We've ranked the best bioinformatics books using expert recommendations, sales data, and millions of reader ratings. At Shortform, we know books. Our book guides are the best in the world. Learn why.
Inheriting the mantle of revolutionary biologist from Darwin, Watson, and Crick, Richard Dawkins forced an enormous change in the way we see ourselves and the world with the publication of The Selfish Gene. Suppose, instead of thinking about organisms using genes to reproduce themselves, as we had since Mendel's work was rediscovered, we turn it around and imagine that "our" genes build and maintain us in order to make more genes. That simple reversal seems to answer many puzzlers which had stumped scientists for years, and we haven't thought of evolution in the same way since.
Why are there miles and miles of "unused" DNA within each of our bodies? Why should a bee give up its own chance to reproduce to help raise her sisters and brothers? With a prophet's clarity, Dawkins told us the answers from the perspective of molecules competing for limited space and resources to produce more of their own kind. Drawing fascinating examples from every field of biology, he paved the way for a serious re-evaluation of evolution. He also introduced the concept of self-reproducing ideas, or memes, which (seemingly) use humans exclusively for their propagation. If we are puppets, he says, at least we can try to understand our strings. --Rob Lightner
"Mukherjee wrote this book for a lay audience, because he knows that the new genome technologies are at the cusp of affecting us all in profound ways," Gates wrote. Mukherjee is what Gates calls a "quadruple threat." He's a practicing physician, teacher, researcher, and author. [source]
Amit Paranjape
@vikramsathaye @DrSidMukherjee @kiranshaw Great book. [source]
Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
Vince Buffalo
4.5
This practical book teaches the skills that scientists need for turning large sequencing datasets into reproducible and robust biological findings. Many biologists begin their bioinformatics training by learning languages like Perl and R alongside the Unix command line. But there’s a huge gap between knowing a few programming languages and being prepared to analyze large amounts of biological data.
Rather than teach bioinformatics as a set of workflows that are likely to change with this rapidly evolving field, this book demsonstrates the practice of bioinformatics through data skills. Rigorous assessment of data quality and of the effectiveness of tools is the foundation of reproducible and robust bioinformatics analysis. Through open source and freely available tools, you’ll learn not only how to do bioinformatics, but how to approach problems as a bioinformatician.
Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Focus on high-throughput (or "next generation") sequencing data Learn data analysis with modern methods, versus covering older theoretical concepts Understand how to choose and implement the best tool for the job Delve into methods that lead to easier, more reproducible, and robust bioinformatics analysis
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Bioinformatics Algorithms: An Active Learning Approach
Phillip Compeau
4.5
Bioinformatics Algorithms: An Active Learning Approach is one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinforma...), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of biology and computer science students alike.
Each chapter begins with a central biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.
The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides.
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Genome: The Autobiography of a Species In 23 Chapters
Matt Ridley
4.5
The human genome, the complete set of genes housed in twenty-three pairs of chromosomes, is nothing less than an autobiography of our species. Spelled out in a billion three-letter words using the four-letter alphabet of DNA, the genome has been edited, abridged, altered and added to as it has been handed down, generation to generation, over more than three billion years. With the first draft of the human genome due to be published in 2000, we, this lucky generation, are the first beings who are able to read this extraordinary book and to gain hitherto unimaginable insights into what it means to be alive, to be human, to be conscious or to be ill.
By picking one newly discovered gene from each of the twenty-three human chromosomes and telling its story, Matt Ridley recounts the history of our species and its ancestors from the dawn of life to the brink of future medicine. He finds genes that we share with bacteria, genes that distinguish us from chimpanzees, genes that can condemn us to cruel diseases, genes that may influence our intelligence, genes that enable us to use grammatical language, genes that guide the development of our bodies and our brains, genes that allow us to remember, genes that exhibit the strange alchemy of nature and nurture, genes that parasitise us for their own selfish ends, genes that battle with one another and genes that record the history of human migrations. From Huntington's disease to cancer, he explores the applications of genetics: the search for understanding and therapy, the horrors of eugenics and the philosophical implications for understanding the paradox of free will.
This book aims to tell a history of humanity from the perspective of genetics rather than sociology. This should complement the other broad histories I've read this year, as well as follow "Energy" well in focusing on science. I've wanted to read Matt Ridley's books for a while. His recent book "The Rational Optimist" about how progress and the economy evolve is also near the top of my ever-growing pile of books to read. [source]
Getting into the more evolution, science kind of books, I really highly, highly recommend picking up Genome … . [source]
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Introduction to Bioinformatics
Arthur Lesk
4.5
Fully revised and updated, the fourth edition of Introduction to Bioinformatics shows how bioinformatics can be used as a powerful set of tools for retrieving and analyzing this biological data, and how bioinformatics can be applied to a wide range of disciplines such as molecular biology, medicine, biotechnology, forensic science, and anthropology. This new edition contains two new chapters, with significantly increased coverage of metabolic pathways, and gene expression and regulation. Written for students without a detailed prior knowledge of programming, this book is the perfect introduction to the field of bioinformatics, providing friendly guidance and advice on how to use various methods and techniques. Additionally, frequent examples, self-test questions, problems, and exercises are incorporated throughout the text to encourage self-directed learning.
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Practical Computing for Biologists
Steven H. D. Haddock and Casey W. Dunn
4.4
Increasingly, scientists find themselves facing exponentially larger data sets and analyses without suitable tools to deal with them. Many biologists end up using spreadsheet programs for most of their data-processing tasks and spend hours clicking around or copying and pasting, and then repeating the process for other data files.
Practical Computing for Biologists shows you how to use many freely available computing tools to work more powerfully and effectively. The book was born out of the authors' own experience in developing tools for their research and helping other biologists with their computational problems. Although many of the techniques are relevant to molecular bioinformatics, the motivation for the book is much broader, focusing on topics and techniques that are applicable to a range of scientific endeavors. Twenty-two chapters organized into six parts address these topics (and more; see Contents):
*Searching with regular expressions
*The Unix command line
*Python programming and debugging
*Creating and editing graphics
*Databases
*Performing analyses on remote servers
*Working with electronics
While most of the concepts and examples apply to any operating system, the main narrative focuses on Mac OS X. Where there are differences for Windows and Linux users, parallel instructions are provided in the margin and in an appendix. The book is designed to be used as a self-guided resource for researchers, a companion book in a course, or as a primary textbook. Practical Computing for Biologists will free you from the most frustrating and time-consuming aspects of data processing so you can focus on the pleasures of scientific inquiry.
RESOURCES
For Students
The Companion Website includes downloads, community forums, tips and examples, and textbook errata and updates.
For Instructors
The Instructor's Resource Library features all of the textbook's figures and tables, provided in ready-to-use PowerPoint presentations.
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A Crack in Creation: Gene Editing and the Unthinkable Power to Control Evolution
Jennifer A. Doudna, Samuel H. Sternberg
4.4
A trailblazing biologist grapples with her role in the biggest scientific discovery of our era: a cheap, easy way of rewriting genetic code, with nearly limitless promise and peril.
Not since the atomic bomb has a technology so alarmed its inventors that they warned the world about its use. Not, that is, until the spring of 2015, when biologist Jennifer Doudna called for a worldwide moratorium on the use of the new gene-editing tool CRISPR—a revolutionary new technology that she helped create—to make heritable changes in human embryos. The cheapest, simplest, most effective way of manipulating DNA ever known, CRISPR may well give us the cure to HIV, genetic diseases, and some cancers, and will help address the world’s hunger crisis. Yet even the tiniest changes to DNA could have myriad, unforeseeable consequences—to say nothing of the ethical and societal repercussions of intentionally mutating embryos to create “better” humans.
Writing with fellow researcher Samuel Sternberg, Doudna shares the thrilling story of her discovery, and passionately argues that enormous responsibility comes with the ability to rewrite the code of life. With CRISPR, she shows, we have effectively taken control of evolution. What will we do with this unfathomable power?
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Recommended by Marvin Liao and Linda Xie.
Marvin Liao
Partner/500 Startups
I tend to jump from book to book and may switch if I am interested in some new topic. This is a pleasure for me (which I also do benefit work wise from too). It’s quite a random list because I have eclectic interests (or just scatterbrained most likely) on tech business, AI, general global economy, geopolitics, rising Biotech economy & history. I'm basically 15% to 50% into all these books. [source]
Linda Xie
Really enjoyed the book "A Crack in Creation" co-authored by Jennifer Doudna, one of the scientists who discovered CRISPR. It goes over the history of gene editing, how it works (gets pretty technical), fascinating experiments, and future implications https://t.co/lM36xJ1BLL [source]
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Molecular Biology of the Cell
Bruce Alberts, Alexander Johnson, Julian Lewis, Martin Raff, Keith Roberts, Peter Walter
4.4
Molecular Biology of the Cell is the classic in-dept text reference in cell biology. By extracting the fundamental concepts from this enormous and ever-growing field, the authors tell the story of cell biology, and create a coherent framework through which non-expert readers may approach the subject. Written in clear and concise language, and beautifully illustrated, the book is enjoyable to read, and it provides a clear sense of the excitement of modern biology. Molecular Biology of the Cell sets forth the current understanding of cell biology (completely updated as of Autumn 2001), and it explores the intriguing implications and possibilities of the great deal that remains unknown. The hallmark features of previous editions continue in the Fourth Edition. The book is designed with a clean and open, single-column layout. The art program maintains a completely consistent format and style, and includes over 1,600 photographs, electron micrographs, and original drawings by the authors. Clear and concise concept headings introduce each section. Every chapter contains extensive references. Most important, every chapter has been subjected to a rigorous, collaborative revision process where, in addition to incorporating comments from expert reviewers, each co-author reads and reviews the other authors' prose. The result is a truly integrated work with a single authorial voice. Features : - Places the latest hot topics sensibly in context - including genomics, protein structure, array technology, stem cells and genetics diseases. - Incorporates and emphasises new genomic data. - All of molecular biology is brought together into one section (chapters 4-7) covering classically defined molecular biology and molecular genetics. - Two chapters deal exclusively with methods and contain information on the latest tools and techniques. - New chapters on "Pathogens, Infection, and Innate Immunity". - Cell Biology Interactive CD-ROM is packaged with every copy of the book. - Contains over 1,600 illustrations, electron micrographs and photographs, of which over 1,000 are originally conceived by the authors.
For many years it has been the best single volume narrative of 'life from scratch.' [source]
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The Double Helix
James Watson
4.3
By identifying the structure of DNA, the molecule of life, Francis Crick and James Watson revolutionized biochemistry & won themselves a Nobel Prize. At the time, Watson was only 24, a young scientist hungry to make his mark. His uncompromisingly honest account of the heady days of their thrilling sprint against other world-class researchers to solve one of science's greatest mysteries gives a dazzlingly clear picture of a world of brilliant scientists with great gifts, very human ambitions & bitter rivalries. With humility unspoiled by false modesty, Watson relates his & Crick's desperate efforts to beat Linus Pauling to the Holy Grail of life sciences, the identification of the basic building block of life. Never has a scientist been so truthful in capturing in words the flavor of his work.
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Recommended by Peter Attia, Matt Ridley, Adam Hart-Davis, and 1 others.
One of the books that considers to be an important read for people interested in his career path. [source]
Matt Ridley
An astonishing literary achievement, and it was about the greatest scientific discovery of the 20th century. [source]
Adam Hart-Davis
They made a brilliant guess and the result was that they and Maurice Wilkins shared a Nobel Prize and Rosalind Franklin didn’t, which was very unfair. [source]
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
Trevor Hastie, Robert Tibshirani, Jerome Friedman
4.3
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book.
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for ``wide'' data (p bigger than n), including multiple testing and false discovery rates.
Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Very comprehensive, sufficiently technical to get most of the plumbing behind machine learning. Very useful as a reference book (actually, there is no other complete reference book). The authors are the real thing (Tibshirani is the one behind the LASSO regularization technique). Uses some mathematical statistics without the burdens of measure theory and avoids the obvious but complicated proofs. I own two copies of this edition, one for the office, one for my house, and the authors generously provide the PDF for travelers like me. [source]
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Medical Terminology & Anatomy for Coding - E-Book
Betsy J. Shiland
4.3
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Long Range Shooting Handbook: The Complete Beginner's Guide to Precision Rifle Shooting
Ryan M Cleckner
4.3
25% of this book's proceeds will be donated to two military charities: the Special Operation Warrior Foundation and the Sua Sponte Foundation. This book is the complete beginner's guide to long range shooting written in simple every-day language so that it's easy to follow. Included are personal tips and best advice from my years of special operations sniper schooling and experience, and as a sniper instructor. If you are an experienced shooter, this guide will be a resource covering the principles and theory of long range shooting. This is the preliminary book to help you understand fundamental concepts such as MOA vs Mils and external ballistics, that can be like a trusted resource at the range. Learning to shoot long range isn't that difficult. Once you understand the basics, you can start to master your technique and you'll be hitting targets in no time. The author has a series of online instructional videos known for their ability to take seemingly complex areas of long range shooting and breaking them down so that they're easy to understand. This book was motivated by the feedback from those videos. The handbook is broken down into three main categories: What it is/How it works, Fundamentals, and How to use it. "What it is/How it works" covers equipment, terminology, and basic principles. "Fundamentals" covers the theory of long range shooting. "How to use it" gives you practical advice on how to implement what you've learned so far to make you a long range shooter.
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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology
Dan Gusfield
4.3
Traditionally an area of study in computer science, string algorithms have, in recent years, become an increasingly important part of biology, particularly genetics. This volume is a comprehensive look at computer algorithms for string processing. In addition to pure computer science, Gusfield adds extensive discussions on biological problems that are cast as string problems and on methods developed to solve them. This text emphasizes the fundamental ideas and techniques central to today's applications. New approaches to this complex material simplify methods that up to now have been for the specialist alone. With over 400 exercises to reinforce the material and develop additional topics, the book is suitable as a text for graduate or advanced undergraduate students in computer science, computational biology, or bio-informatics.
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Data Science from Scratch: First Principles with Python
Joel Grus
4.3
To really learn data science, you should not only master the tools--data science libraries, frameworks, modules, and toolkits--but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.
If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today's messy glut of data.
* Get a crash course in Python * Learn the basics of linear algebra, statistics, and probability--and how and when they're used in data science * Collect, explore, clean, munge, and manipulate data * Dive into the fundamentals of machine learning * Implement models such as k-nearest neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering * Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
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Recommended by Balaji S. Srinivasan and Thorsten Heller.
Thorsten Heller
The Best #book to Start your #DataScience Journey - Towards #DataScience https://t.co/D8PlkkSxw6 by @benthecoder1 [source]
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Understanding Bioinformatics
Marketa Zvelebil and Jeremy Baum
4.3
Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics provides a definitive guide to this vibrant and evolving discipline. The book takes a conceptual approach. It guides the reader from first principles through to an understanding of the computational techniques and the key algorithms. Understanding Bioinformatics is an invaluable companion for students from their first encounter with the subject through to more advanced studies.
The book is divided into seven parts, with the opening part introducing the basics of nucleic acids, proteins and databases. Subsequent parts are divided into 'Applications' and 'Theory' Chapters, allowing readers to focus their attention effectively. In each section, the Applications Chapter provides a fast and straightforward route to understanding the main concepts and 'getting started'. Each of these is then followed by Theory Chapters which give greater detail and present the underlying mathematics. In Part 2, Sequence Alignments, the Applications Chapter shows the reader how to get started on producing and analyzing sequence alignments, and using sequences for database searching, while the next two chapters look closely at the more advanced techniques and the mathematical algorithms involved. Part 3 covers evolutionary processes and shows how bioinformatics can be used to help build phylogenetic trees. Part 4 looks at the characteristics of whole genomes. In Parts 5 and 6 the focus turns to secondary and tertiary structure - predicting structural conformation and analysing structure-function relationships. The last part surveys methods of analyzing data from a set of genes or proteins of an organism and is rounded off with an overview of systems biology.
The writing style of Understanding Bioinformatics is notable for its clarity, while the extensive, full-color artwork has been designed to present the key concepts with simplicity and consistency. Each chapter uses mind-maps and flow diagrams to give an overview of the conceptual links within each topic.
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Pattern Recognition and Machine Learning
Christopher M. Bishop
4.3
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation. Similarly, new models based on kernels have had a significant impact on both algorithms and applications. This new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Knowledge of multivariate calculus and basic linear algebra is required, and some familiarity with probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
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An Introduction to Systems Biology: Design Principles of Biological Circuits
Uri Alon
4.3
Written for students and researchers in systems biology, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological networks, highlighting simple, recurring circuit elements that make up the network. Rigorously classroom-tested, it contains new additions as well as corrections and revisions for better flow. This edition includes four new chapters: Perfect Robustness, Scaling in Development, Noise and Variability in Biological Circuits, and Evolution of Modularity. It also doubles the number of exercises and adds an appendix.
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R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics
Paul Teetor
4.3
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.
Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an experienced data programmer, it will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.
Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language--one practical example at a time."--Jeffrey Ryan, software consultant and R package author
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The Epigenetics Revolution
Nessa Carey
4.3
Nessa Carey presents a compelling story of the most important revolution in modern biology - and what it could mean for humanity. She concludes by investigating the amazing possibilities for the improvement of humankind that epigenetics offers for the surprisingly near future.
I love the book on epigenetics, a book called "Epigenetics Revolution". [source]
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Biological Sequence Analysis
Richard Durbin
4.2
Probablistic models are becoming increasingly important in analyzing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analyzing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it is accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time presents the state of the art in this new and important field.
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Plant Based Meal Plan Cookbook: 500 Quick & Easy Everyday Recipes for Busy People on A Plant Based Diet | 21-Day Plant-Based Meal Plan (Plant-Based Diet Cookbooks)
Jennifer Bolton
4.2
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Who We Are and How We Got Here: Ancient DNA and the New Science of the Human Past
David Reich
4.2
A groundbreaking book about how technological advances in genomics and the extraction of ancient DNA have profoundly changed our understanding of human prehistory while resolving many long-standing controversies.
Massive technological innovations now allow scientists to extract and analyze ancient DNA as never before, and it has become clear--in part from David Reich's own contributions to the field--that genomics is as important a means of understanding the human past as archeology, linguistics, and the written word. Now, in The New Science of the Human Past, Reich describes with unprecedented clarity just how the human genome provides not only all the information that a fertilized human egg needs to develop but also contains within it the history of our species. He delineates how the Genomic Revolution and ancient DNA are transforming our understanding of our own lineage as modern humans; how genomics deconstructs the idea that there are no biologically meaningful differences among human populations (though without adherence to pernicious racist hierarchies); and how DNA studies reveal the deep history of human inequality--among different populations, between the sexes, and among individuals within a population.
I will write a longer review, but this is a monument, not just a book. And the beginning of a new cultural program. On a scale of 0 to 100, paternity tests count as 99.99 and written/oral history should count for .01. Apply that to populations. That’s plain statistics/probability. We are seeing science in action: information theory displaces BS, the handwaving just so stories we got from historians. [source]
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Medical Terminology & Anatomy for Coding
Betsy J. Shiland
4.2
Medical Terminology and Anatomy for Coding, 3rd Edition is unlike any other medical terminology textbook on the market. By interspersing ICD-10 and CPT coding guidelines and notes, electronic medical records, and integrated exercises, it combines anatomy and physiology coverage with the latest medical terminology coders - and coding students - need. The ICD-10-CM classification system serves as the structure for organizing diseases and disorders, with carefully drawn, well-labeled illustrations to help you visualize the associated anatomy. A new Basics of Oncology appendix provides the terminology and physiology of neoplasms, and new CPT coding information indicates where physician coding differs from ICD-10 coding. The robust Evolve site includes games, activities, and animations to reinforce learning.
UNIQUE!Medical terminology, anatomy and physiology specifically tailored to ICD-10-CM and ICD-10-PCS coding manualssupply you with an excellent foundation for learning the medical terminology related to coding. UNIQUE!ABody Part key provides a complete list of body parts and how they should be coded in ICD-10.
UNIQUE!Pathology terms organized by ICD-10 disease and disorder categories let you learn terms in the same order they are presented in the coding manual.
UNIQUE! Guideline Alert! and Special Notes boxes highlight relevant ICD-10 information.
UNIQUE! Pharmacology in each body system and a Pharmacology Basics appendix help you recognize drugs and medications in medical reports.
Procedural terms supply a more complete picture of the number and kind of procedures you will encounter on medical reports.
UNIQUE! Normal Lab Values appendix familiarizes you with normal and abnormal lab values so you know when to search a medical record for possible additional diagnoses.
UNIQUE!Root operation tables illustrate the root operations in PCS and their associated suffixes.
Pathology and procedure terminology tables list the word parts for each term, along with the definition so you become familiar with prefixes, suffixes, and combining forms.
Exercises interspersed throughout the text encourage you to practice and learn as you move through the material.
Be Careful! boxes warn you about similar and potentially confusing word parts and medical terms.
Electronic medical record format illustrates the appearance of electronic records now being used in many healthcare settings.
NEW! CPT coding information indicates where physician coding differs from ICD-10 coding. NEW and EXAPNDED! New chapter that incorporates pregnancy, perinatal, and congenital conditions to more closely match the ICD-10 manual.
NEW and UNIQUE! Oncology Basics appendix provides the terminology and physiology of neoplasms that you need to understand.
NEW and UNIQUE! Generic and brand drug namestable keeps you in the know.
NEW and EXPANDED! The online course (MTO) now includes adaptive learning, gradable case studies, and audio reviews to provide a complete learning experience for distance learners.
UPDATED! Evolve student resources now report to the gradebook so you can practice medical terminology in an interactive setting and instructors can follow your progress.
NEW! Updated ICD-10 guidelines and notes provide up-to-the-minute coding information.
NEW! Updated terminology reflects current technology and ICD-10 manual terms.
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Introducing Epigenetics: A Graphic Guide (Introducing...)
Cath Ennis
4.2
Epigenetics is the most exciting field in biology today, developing our understanding of how and why we inherit certain traits, develop diseases and age, and evolve as a species.
This non-fiction comic book introduces us to genetics, cell biology and the fascinating science of epigenetics, which is rapidly filling in the gaps in our knowledge, allowing us to make huge advances in medicine. We’ll look at what identical twins can teach us about the epigenetic effects of our environment and experiences, why certain genes are 'switched on' or off at various stages of embryonic development, and how scientists have reversed the specialization of cells to clone frogs from a single gut cell.
In Introducing Epigenetics, Cath Ennis and Oliver Pugh pull apart the double helix, examining how the epigenetic building blocks and messengers that interpret and edit our genes help to make us, well, us.
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Biyoenformatik 1
Mehmet Keçeci
4.2
Tam Renkli-Full Color Biyoenformatige Giris: Introduction to Bioinformatics: Biyoenformatik, Biyobilisim, Bioinformatics dersi hizla yukselmis olan bilisimin temel bilimlerde kullanimi da dogal olarak artamasi sonucu özellikle biyolojik olaylarin cok fazla parametreye bagli olmasi, uzun surecler icermesi gibi karmasik, kompleks olaylarin cozumu ve bunlarin depolanmasi, yorumlanmasi ve bir sonuca kisa zamanda varilabilmesi icin ortaya cikmis bir bilim ve disiplin dalidir. Her iki bilim dalininda birbirlerine icerik olarak uzak olmasi bu bilim dallarinin ayni anda her iki dala da verilmesinin guclugunu ortadan kaldirmak icin Biyoenformatigin bir disiplin olarak verilmesinin zaruretini dogurmustur. Biyoenformatik, Biyobilisim (Bioinformatics): Biyolojik bilimsel (biyobilimsel, bioscientific) verilerin toplanmasi, islenmesi, anlamli hale getirilmesi ve bunlarin icindeki veya etrafindaki problemlerin tesbiti, bulunmasi, irdelenmesi, anlasilmasi ve bunlara cözum uretimi icin gelistirilmis sanal ortam algisini (In Silico, Silicio, in Glass) canlilik (in Vivo), gerceklik ve realiteyi daha iyi anlamamiza yardimci olan bir disiplin dalidir. Mehmet Kececi, 21.03.2015.
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Python for Biologists: A Complete Programming Course for Beginners
Dr Martin Jones
4.2
Learning to program is one of the best investments that you can make for your research and your career. Python for biologists is a complete programming course for beginners that will give you the skills you need to tackle common biological and bioinformatics problems.
Why learn programming?
Maybe you see colleagues writing programs to save time and deal with large datasets. Maybe your supervisor has told you that you need to learn programming for your next project. Maybe you've been looking at job ads and noticed just how many of them are asking for programming skills.
Table of contents
In chapter one, you'll learn why Python is a good choice for biologists and beginners alike. You'll also learn how to install Python for your operating system and how to set up your programming environment, complete with links to all the free software you'll need. In chapter two, you'll learn how to manipulate text (including DNA and protein sequences) and how to fix errors in your programs. Exercises: calculating AT content, splicing introns. In chapter three, you'll learn how to read and write data to and from files. You'll also learn how to deal with file paths and the FASTA file format.Exercises: splitting genomic DNA, writing a FASTA file. In chapter four, you'll learn how to process many pieces of data in a single program and more advanced tools for sequence manipulation. Exercises: trimming adapter sequences, concatenating exons. In chapter five, you'll learn how to make Python even more useful by creating your own functions, including the best ways to test those functions in order to speed up development. Exercises: Analyzing the amino acid composition of protein sequences. In chapter six, you'll learn how to write programs that can make smart decisions about how to handle data and how to make your programs follow complex rules. Exercises: filtering genes based on multiple criteria. In chapter seven, you'll learn an incredibly powerful tool for working with patterns in text - regular expressions - and how to use it to search in DNA and protein sequences. Exercises: filtering accession names and calculating restriction fragment sizes. In chapter eight, you'll learn how to store huge amounts of data in a way that can still allows it to be retrived very efficiently. This allows simplification of much of the code from previous chapters. Exercises: translating DNA sequences to protein. In chapter nine, you'll learn how to make your Python programs work in harmony with existing tools, and how to polish up your programs so that they're ready for other people to use. Exercises: counting k-mers, binning DNA sequences by length.
About the author
Dr. Martin Jones has been teaching biologists to write software for over five years and has taught everyone from postgraduates to PIs. He is currently Lecturer in Bioinformatics at Edinburgh University.
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Introduction to Proteins: Structure, Function, and Motion (Chapman & Hall/CRC Mathematical & Computational Biology)
Amit Kessel
4.2
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An Introduction to Bioinformatics Algorithms
Neil C. Jones, Pavel A. Pevzner
4.2
An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics.
This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.
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Common Core Practice - 8th Grade English Language Arts: Workbooks to Prepare for the PARCC or Smarter Balanced Test: CCSS Aligned
Ace Academic Publishing
4.2
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Bioinformatics and Functional Genomics
Jonathan Pevsner
4.2
Wiley is proud to announce the publication of the first ever broad-based textbook introduction to Bioinformatics and Functional Genomics by a trained biologist, experienced researcher, and award-winning instructor. In this new text, author Jonathan Pevsner, winner of the 2001 Johns Hopkins University "Teacher of the Year" award, explains problem-solving using bioinformatic approaches using real examples such as breast cancer, HIV-1, and retinal-binding protein throughout. His book includes 375 figures and over 170 tables. Each chapter includes: Problems, discussion of Pitfalls, Boxes explaining key techniques and math/stats principles, Summary, Recommended Reading list, and URLs for freely available software. The text is suitable for professionals and students at every level, including those with little to no background in computer science.
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Learning Python
Mark Lutz
4.2
Portable, powerful, and a breeze to use, Python is the popular open source object-oriented programming language used for both standalone programs and scripting applications. Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.
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Junk DNA: A Journey Through the Dark Matter of the Genome
Nessa Carey
4.2
From the author of the acclaimed The Epigenetics Revolution ('A book that would have had Darwin swooning' - Guardian) comes another thrilling exploration of the cutting edge of human science. For decades after the structure of DNA was identified, scientists focused purely on genes, the regions of the genome that contain codes for the production of proteins. Other regions - 98% of the human genome - were dismissed as 'junk'. But in recent years researchers have discovered that variations in this 'junk' DNA underlie many previously intractable diseases, and they can now generate new approaches to tackling them. Nessa Carey explores, for the first time for a general audience, the incredible story behind a controversy that has generated unusually vituperative public exchanges between scientists. She shows how junk DNA plays an important role in areas as diverse as genetic diseases, viral infections, sex determination in mammals, human biological complexity, disease treatments, even evolution itself - and reveals how we are only now truly unlocking its secrets, more than half a century after Crick and Watson won their Nobel prize for the discovery of the structure of DNA in 1962.
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Molecular Biology of the Cell: The Problems Book
Tim Hunt and John Wilson
4.2
The Problems Book helps students appreciate the ways in which experiments and simple calculations can lead to an understanding of how cells work by introducing the experimental foundation of cell and molecular biology. Each chapter reviews key terms, tests for understanding basic concepts, and poses research-based problems. The Problems Book has been designed to correspond with the first twenty chapters of Molecular Biology of the Cell, Sixth Edition.
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The Patient Will See You Now: The Future of Medicine is in Your Hands
Eric Topol
4.2
A trip to the doctor is almost a guarantee of misery. You'll make an appointment months in advance. You'll probably wait for several hours until you hear "the doctor will see you now"—but only for fifteen minutes! Then you'll wait even longer for lab tests, the results of which you'll likely never see, unless they indicate further (and more invasive) tests, most of which will probably prove unnecessary (much like physicals themselves). And your bill will be astronomical.
In The Patient Will See You Now, Eric Topol, one of the nation’s top physicians, shows why medicine does not have to be that way. Instead, you could use your smartphone to get rapid test results from one drop of blood, monitor your vital signs both day and night, and use an artificially intelligent algorithm to receive a diagnosis without having to see a doctor, all at a small fraction of the cost imposed by our modern healthcare system.
The change is powered by what Topol calls medicine's "Gutenberg moment." Much as the printing press took learning out of the hands of a priestly class, the mobile internet is doing the same for medicine, giving us unprecedented control over our healthcare. With smartphones in hand, we are no longer beholden to an impersonal and paternalistic system in which "doctor knows best." Medicine has been digitized, Topol argues; now it will be democratized. Computers will replace physicians for many diagnostic tasks, citizen science will give rise to citizen medicine, and enormous data sets will give us new means to attack conditions that have long been incurable. Massive, open, online medicine, where diagnostics are done by Facebook-like comparisons of medical profiles, will enable real-time, real-world research on massive populations. There's no doubt the path forward will be complicated: the medical establishment will resist these changes, and digitized medicine inevitably raises serious issues surrounding privacy. Nevertheless, the result—better, cheaper, and more human health care—will be worth it.
Provocative and engrossing, The Patient Will See You Now is essential reading for anyone who thinks they deserve better health care. That is, for all of us.
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Recommended by Elad Yom-Tov.
Elad Yom-Tov
The thesis is that since you can now have all of your data online, it empowers the patient to be a bigger player in medicine. [source]
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Python Machine Learning Cookbook - Second Edition
Giuseppe Ciaburro and Prateek Joshi
4.2
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Molecular Data Analysis Using R
Csaba Ortutay
4.2
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Laws, Language and Life: Howard Pattee S Classic Papers on the Physics of Symbols with Contemporary Commentary
Howard Hunt Pattee
4.2
Howard Pattee is a physicist who for many years has taken his own path in studying the physics of symbols, which is now a foundation for biosemiotics. By extending von Neumann s logical requirements for self-replication, to the physical requirements of symbolic instruction at the molecular level, he concludes that a form of quantum measurement is necessary for life. He explains why all non-dynamic symbolic and informational controls act as special (allosteric) constraints on dynamical systems. Pattee also points out that symbols do not exist in isolation but in coordinated symbol systems we call languages. Such insights turn out to be necessary to situate biosemiotics as an objective scientific endeavor. By proposing a way to relate quiescent symbolic constraints to dynamics, Pattee s work builds a bridge between physical, biological, and psychological models that are based on dynamical systems theory. Pattee s work awakes new interest in cognitive scientists, where his recognition of the necessary separation the epistemic cut between the subject and object provides a basis for a complementary third way of relating the purely symbolic, computational models of cognition and the purely dynamic, non-representational models. This selection of Pattee s papers also addresses several other fields, including hierarchy theory, artificial life, self-organization, complexity theory, and the complementary epistemologies of the physical and biological sciences."
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Learn AWS Serverless Computing: A beginner's guide to using AWS Lambda, Amazon API Gateway, and services from Amazon Web Services
Scott Patterson
4.2
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Python: - The Bible- 3 Manuscripts in 1 Book: -Python Programming for Beginners -Python Programming for Intermediates -Python Programming for Advanced
Maurice J. Thompson
4.2
This Box Set Includes 3 Books: Python Programming For Beginners - Learn The Basics Of Python In 7 Days! Python Programming For Intermediates - Learn The Basics Of Python In 7 Days! Python Programming For Advanced - Learn The Basics Of Python In 7 Days!
Python Programming For Beginners - Learn The Basics Of Python In 7 Days! Here's what you'll learn from this book: ✓Introduction ✓Understanding Python: A Detailed Background ✓How Python Works ✓Python Glossary ✓How to Download and Install Python ✓Python Programming 101: Interacting With Python in Different Ways ✓How to Write Your First Python Program ✓Variables, Strings, Lists, Tuples, Dictionaries ✓About User-Defined Functions ✓How to Write User-Defined Functions in Python ✓About Coding Style ✓Practice Projects: The Python Projects for Your Practice
Python Programming For Intermediates - Learn The Basics Of Python In 7 Days! Here's what you'll learn from this book: ✓ Shallow copy and deep copy ✓ Objects and classes in Python
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Hands-On Microservices with Spring Boot and Spring Cloud: Build and deploy Java microservices using Spring Cloud, Istio, and Kubernetes
Magnus Larsson
4.2
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R Graphics Cookbook: Practical Recipes for Visualizing Data
Winston Chan
4.2
This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R's graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works.
Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you're ready to get started.
Use R's default graphics for quick exploration of data Create a variety of bar graphs, line graphs, and scatter plots Summarize data distributions with histograms, density curves, box plots, and other examples Provide annotations to help viewers interpret data Control the overall appearance of graphics Render data groups alongside each other for easy comparison Use colors in plots Create network graphs, heat maps, and 3D scatter plots Structure data for graphing
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Advanced Python for Biologists
Dr Martin O Jones
4.2
Advanced Python for Biologists is a programming course for workers in biology and bioinformatics who want to develop their programming skills. It starts with the basic Python knowledge outlined in Python for Biologists and introduces advanced Python tools and techniques with biological examples. You'll learn: - How to use object-oriented programming to model biological entities - How to write more robust code and programs by using Python's exception system - How to test your code using the unit testing framework - How to transform data using Python's comprehensions - How to write flexible functions and applications using functional programming - How to use Python's iteration framework to extend your own object and functions Advanced Python for Biologists is written with an emphasis on practical problem-solving and uses everyday biological examples throughout. Each section contains exercises along with solutions and detailed discussion.
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Human Molecular Genetics
Tom Strachan and Andrew Read
4.2
Human Molecular Genetics has been carefully crafted over successive editions to provide an authoritative introduction to the molecular aspects of human genetics, genomics and cell biology.
Maintaining the features that have made previous editions so popular, this fifth edition has been completely updated in line with the latest developments in the field. Older technologies such as cloning and hybridization have been merged and summarized, coverage of newer DNA sequencing technologies has been expanded, and powerful new gene editing and single-cell genomics technologies have been added. The coverage of GWAS, functional genomics, stem cells, and disease modeling has been expanded. Greater focus is given to inheritance and variation in the context of populations and on the role of epigenetics in gene regulation.
Key features:
Fully integrated approach to the molecular aspects of human genetics, genomics, and cell biology
Accessible text is supported and enhanced throughout by superb artwork illustrating the key concepts and mechanisms
Summary boxes at the end of each chapter provide clear learning points
Annotated further reading helps readers navigate the wealth of additional information in this complex subject and provides direction for further study
Reorganized into five sections for improved access to related topics
Also new to this edition - brand new chapter on evolution and anthropology from the authors of the highly acclaimed Human Evolutionary Genetics
A proven and popular textbook for upper-level undergraduates and graduate students, the new edition of Human Molecular Genetics remains the 'go-to' book for those studying human molecular genetics or genomics courses around the world.
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The CAHIMS Review Guide (HIMSS Book Series)
Joanne Himss
4.2
HIMSS’ Certified Associate in Healthcare Information and Management Systems (CAHIMS) certification offers a pathway to careers in health information technology (health IT) for associate-level, emerging professionals, or those who would like to transition to health IT from other industries. The CAHIMS Review Guide, 2nd Edition is the ideal resource for those preparing for the CAHIMS certification exam―or looking for a comprehensive "health IT 101" guide.Content in this updated and revised CAHIMS review guide reflects the new CAHIMS exam content outline. Content is divided into three topic categories: organizational and technology environments; systems analysis, design, selection, implementation, support, maintenance, testing, evaluation, privacy, and security; and leadership and management support. Each chapter includes learning objectives for tracking progress in understanding and articulating the content. Practice exam questions at the end of the book reinforce key concepts explored throughout the book.This book is a comprehensive and timely introduction to healthcare information and management systems. It’s also an invaluable resource for staying current in all aspects of the industry. In addition to sample exam questions, this book includes an overview of the eligibility requirements, testing procedures, and the CAHIMS examination itself.
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Essential Bioinformatics
Jin Xiong
4.2
Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.
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Conversations with the Future: 21 Visions for the 21st Century
Nikola Danaylov
4.2
For generations, humanity stared at the vastness of the oceans and wondered, "What if?" Today, having explored the curves of the Earth, we now stare at endless stars and wonder, "What if?" Our technology has brought us to the make-or-break moment in human history. We can either grow complacent, and go extinct like the dinosaurs, or spread throughout the cosmos, as Carl Sagan dreamed of.What if your toothbrush becomes smarter than you? What happens to your business, your country, your planet and yourself? What if your car doesn't need a driver anymore? What if we don't need to age and die? What if machines are smarter than us? What if, instead of fear of the future - you see opportunity, instead of an end - you see a beginning, instead of loss - you see profit, and instead of death - you see life? What if you and your organization get future-primed?For many years Nikola Danaylov has been interviewing the future and motivating people all over the world to embrace rather than fear it. "Conversations with the Future" was born from those interviews and Nik's unceasing need to explore "What If" with some of the most forward thinking visionaries in the world today.
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Instant Pot Air Fryer Crisp Cookbook #2020: 700+ Affordable, Quick, Easy and Delicious Recipes for Your Pressure Cooker and Air Fryer Crisp Pot
Jacqueline Barnard
4.2
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Bioinformatics for Biologists
Pavel Pevzner, Ron Shamir
4.1
The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors each a leading scientist engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers.
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Statistical Methods in Bioinformatics: An Introduction
Warren J. Ewens, Gregory R. Grant
4.1
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community.
This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods.
The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized.
The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text.
Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science.
Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999.
Comments on the first edition:
"This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics)
"Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften)
"The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association)
"The authors have restructured classical material to a great extent and the new organization of the
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Bioinformatics For Dummies
Jean-Michel Claverie, Cedric Notredame
4.1
Were you always curious about biology but were afraid to sit through long hours of dense reading? Did you like the subject when you were in high school but had other plans after you graduated? Now you can explore the human genome and analyze DNA without ever leaving your desktop! Bioinformatics For Dummies is packed with valuable information that introduces you to this exciting new discipline. This easy-to-follow guide leads you step by step through every bioinformatics task that can be done over the Internet. Forget long equations, computer-geek gibberish, and installing bulky programs that slow down your computer. You'll be amazed at all the things you can accomplish just by logging on and following these trusty directions. You get the tools you need to:
Analyze all types of sequences Use all types of databases Work with DNA and protein sequences Conduct similarity searches Build a multiple sequence alignment Edit and publish alignments Visualize protein 3-D structures Construct phylogenetic trees This up-to-date second edition includes newly created and popular databases and Internet programs as well as multiple new genomes. It provides tips for using servers and places to seek resources to find out about what's going on in the bioinformatics world. Bioinformatics For Dummies will show you how to get the most out of your PC and the right Web tools so you'll be searching databases and analyzing sequences like a pro!
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Biopunk: Kitchen-Counter Scientists Hack the Software of Life
Marcus Wohlsen
4.1
Bill Gates recently told Wired that if he were a teenager today, he would be hacking biology. "If you want to change the world in some big way," he says, "that's where you should start-biological molecules." The most disruptive force on the planet resides in DNA. Biotech companies and academic researchers are just beginning to unlock the potential of piecing together life from scratch. Champions of synthetic biology believe that turning genetic code into Lego-like blocks to build never-before-seen organisms could solve the thorniest challenges in medicine, energy, and environmental protection. But as the hackers who cracked open the potential of the personal computer and the Internet proved, the most revolutionary discoveries often emerge from out-of-the-way places, forged by brilliant outsiders with few resources besides boundless energy and great ideas. In "Biopunk," Marcus Wohlsen chronicles a growing community of DIY scientists working outside the walls of corporations and universities who are committed to democratizing DNA the way the Internet did information. The "biohacking" movement, now in its early, heady days, aims to unleash an outbreak of genetically modified innovation by making the tools and techniques of biotechnology accessible to everyone. Borrowing their idealism from the worlds of open-source software, artisinal food, Internet startups, and the Peace Corps, biopunks are devoted advocates for open-sourcing the basic code of life. They believe in the power of individuals with access to DNA to solve the world's biggest problems. You'll meet a new breed of hackers who aren't afraid to get their hands wet, from entrepreneurs who aim to bring DNA-based medical tools to the poorest of the poor to a curious tinkerer who believes a tub of yogurt and a jellyfish gene could protect the world's food supply. These biohackers include: - A duo who started a cancer drug company in their kitchen - A team who built an open-source DNA copy machine - A woman who developed a genetic test in her apartment for a deadly disease that had stricken her family Along with the potential of citizen science to bring about disruptive change, Wohlsen explores the risks of DIY bioterrorism, the possibility of genetic engineering experiments gone awry, and whether the ability to design life from scratch on a laptop might come sooner than we think.
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Recommended by Balaji S. Srinivasan.
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Genetic Data Analysis for Plant and Animal Breeding
Fikret Isik, James Holland, and Christian Maltecca
4.1
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Beginning Perl for Bioinformatics
James Tisdall
4.1
With its highly developed capacity to detect patterns in data, Perl has become one of the most popular languages for biological data analysis. But if you're a biologist with little or no programming experience, starting out in Perl can be a challenge. Many biologists have a difficult time learning how to apply the language to bioinformatics. The most popular Perl programming books are often too theoretical and too focused on computer science for a non-programming biologist who needs to solve very specific problems.Beginning Perl for Bioinformatics is designed to get you quickly over the Perl language barrier by approaching programming as an important new laboratory skill, revealing Perl programs and techniques that are immediately useful in the lab. Each chapter focuses on solving a particular bioinformatics problem or class of problems, starting with the simplest and increasing in complexity as the book progresses. Each chapter includes programming exercises and teaches bioinformatics by showing and modifying programs that deal with various kinds of practical biological problems. By the end of the book you'll have a solid understanding of Perl basics, a collection of programs for such tasks as parsing BLAST and GenBank, and the skills to take on more advanced bioinformatics programming. Some of the later chapters focus in greater detail on specific bioinformatics topics. This book is suitable for use as a classroom textbook, for self-study, and as a reference.The book covers:
Programming basics and working with DNA sequences and strings Debugging your codeSimulating gene mutations using random number generatorsRegular expressions and finding motifs in dataArrays, hashes, and relational databasesRegular expressions and restriction mapsUsing Perl to parse PDB records, annotations in GenBank, and BLAST output
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The Molecules of Life
John Kuriyan
4.1
This textbook provides an integrated physical and biochemical foundation for undergraduate students majoring in biology or health sciences. It is particularly suitable for students planning to enter the pharmaceutical industry. This new generation of molecular biologists and biochemists will harness the tools and insights of physics and chemistry to exploit the emergence of genomics and systems-level information in biology, and will shape the future of medicine.
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Principles of Population Genetics
Daniel L. Hartl, Andrew G. Clark
4.1
Principles of Population Genetics, Third Edition, provides a balanced presentation of theory and observation for students at the undergraduate and graduate levels. In response to suggestions from students and instructors, the book has been trimmed more than 100 pages and rewritten with the goal to optimize its use as a teaching aid. It introduces the principles of genetics and statistics that are relevant to population studies, and examines the forces affecting genetic variation from the molecular to the organismic level. Integrated throughout the book are descriptions of molecular methods used to study variation in natural populations, as well as explanations of the relevant estimation theory using actual data. Chapter 1 presents the fundamental genetic and statistical concepts in population genetics. Chapter 2 reviews the types and prevalence of genetic variation in natural populations. This is followed in Chapter 3 by a detailed examination of the implications of random mating for one locus and multiple loci. Chapter 4 examines population subdivision and its consequences for the distribution of genetic variation among subpopulations, including the hierarchical F statistics used in estimating these effects. Chapters 5 through 7 deal with mutation, migration, natural selection in all its varieties, and the consequences of random genetic drift. Molecular population genetics, including coalescent theory, is the subject of Chapter 8. Quantitative genetics is covered in Chapter 9, from the standpoint of genetic variance and covariance components as well as with respect to molecular markers used to detect quantitative trait loci (QTLs). Applications of principles discussed in thetext are illustrated by numerous examples of worked problems, using actual data. Each chapter end, in addition to a complete summary, offers several problems for solution, to reinforce and further develop the concepts.
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Introduction to Mathematical Methods in Bioinformatics
Alexander Isaev
4.1
This book looks at the mathematical foundations of the models currently in use. All existing books on bioinformatics are software-orientated and they concentrate on computer implementations of mathematical models of biology. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.
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MATLAB: A Practical Introduction to Programming and Problem Solving
Stormy Attaway Ph.D. Boston…
4.1
MATLAB: A Practical Introduction to Programming and Problem Solving, Fourth Edition, winner of a 2017 Textbook Excellence Award (Texty), has been updated to reflect the functionality of the current version of MATLAB, including the new H2 Graphics system. It features new and revised end-of-chapter exercises, more engineering applications to help the reader learn this software tool in context, and a new section on object-oriented programming in MATLAB. MATLAB has become the standard software tool for solving scientific and engineering problems due to its powerful built-in functions and its ability to program.
Assuming no knowledge of programming, this book guides the reader through both programming and built-in functions to easily exploit MATLAB's extensive capabilities for tackling engineering problems. The book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. In-depth coverage is given to input/output, a topic fundamental to many engineering applications.
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Artificial Intelligence for Improved Patient Outcomes: Principles for Moving Forward with Rigorous Science
DANIEL W. BYRNE
4.1
Artificial Intelligence for Improved Patient Outcomes provides new, relevant, and practical information on what AI can do in healthcare and how to assess whether AI is improving health outcomes. With clear insights and a balanced approach, this innovative book offers a one-stop guide on how to design and lead pragmatic real-world AI studies that yield rigorous scientific evidence—all in a manner that is safe and ethical. Daniel Byrne, Director of Artificial Intelligence Research at AVAIL (the Advanced Vanderbilt Artificial Intelligence Laboratory) and author of landmark pragmatic studies published in leading medical journals, shares four decades of experience as a biostatistician and AI researcher. Building on his first book, Publishing Your Medical Research, the author gives the reader the competitive advantage in creating reproducible AI research that will be accepted in prestigious high-impact medical journals. Provides easy-to-understand explanations of the key concepts in using and evaluating AI in medicine. Offers practical, actionable guidance on the mechanics and implementation of AI applications in medicine. Shares career guidance on a successful future in AI in medicine. Teaches the skills to evaluate AI tools and avoid being misled by the hype. For a wide audience of healthcare professionals impacted by Artificial Intelligence in medicine, including physician-scientists, AI developers, entrepreneurs, and healthcare leaders who need to evaluate AI applications designed to improve safety, quality, and value for their institutions. Enrich Your eBook Reading Experience Read directly on your preferred device(s), such as computer, tablet, or smartphone. Easily convert to audiobook, powering your content with natural language text-to-speech.
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Genetics 101: From Chromosomes and the Double Helix to Cloning and DNA Tests, Everything You Need to Know about Genes (Adams 101)
Beth Skwarecki
4.1
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How Nature Works: The Science of Self-Organized Criticality
Per Bak
4.1
and acknowledgments Self-organized criticality is a new way of viewing nature. The basic picture is one where nature is perpetually out of balance, but organized in a poised state-the critical state-where anything can happen within well-defined statistical laws. The aim of the science of self-organized criticality is to yield insight into the fundamental question of why nature is complex, not simple, as the laws of physics imply. Self-organized criticality explains some ubiquitous patterns existing in nature that we view as complex. Fractal structure and catastrophic events are among those regularities. Applications range from the study of pulsars and black holes to earthquakes and the evolution of life. One intriguing conse- quence of the theory is that catastrophes can occur for no reason whatsoever. Mass extinctions may take place without any external triggering mechanism such as a volcanic eruption or a meteorite hitting the earth (although the the- ory of course cannot rule out that this has in fact occurred). xu How Nature Works Since we first proposed the idea in 1987, more than 2, ooo papers have been written on self-organized criticality, making ours the most cited paper in physics during that period. How Nature Works is the first book to deal with the subject. The basic idea is simple, and most of the mathematical models that have been used in the implementation of the theory are not complicated.
This book is a great attempt at finding some universality based on systems in a "critical" state, with departures from such state taking place in a manner that follows power laws. The sandpile is a great baby model for that. Some people are critical of Bak's approach, some even suggesting that we may not get power laws in these "sandpile" effects, but something less scalable in the tails. The point is :so what? The man has vision. I looked at the reviews of this book. Clearly a few narrow-minded scientists do not seem to like it (many did not like Per Bak's ego). But the book is remarkably intuitive and the presentation is so clear that he takes you by the hand. It is even entertaining. If you are looking to find flaws in his argument his pedagogy allows it (it is immediately obvious to us who dabble with simulations of these processes that you need an infinite sandpile to get a pure power law). Another problem. I have been ordering the book on Amazon for ages. Copernicus books does not respond to emails. I got my copy at the NYU library. Bak passed away 2 years ago and nobody seems to be pushing for his interest and that of us his readers (for used books to sell for 99 implies some demand). This convinces me NEVER to publish with Springer. [source]
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Statistical Analysis of Network Data: Methods and Models (Springer Series in Statistics)
Eric D. Kolaczyk
4.1
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Learning R: A Step-By-Step Function Guide to Data Analysis
Richard Cotton
4.1
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.
The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code.
Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code
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Mastering Windows PowerShell Scripting: Automate and manage your environment using PowerShell Core 6.0, 3rd Edition
Chris Dent
4.1
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Health Informatics: Practical Guide
William Hersh
4.1
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Genomics and Personalized Medicine: What Everyone Needs to Know®
Michael Snyder
4.1
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Genetics for Dummies
Tara Rodden Robinson
4.1
Reveals the connections between genetics and specific diseases Understand the science and the ethics behind genetics
Want to know more about genetics? This non-intimidating guide gets you up to speed on all the fundamentals. From dominant and recessive inherited traits to the DNA double-helix, you get clear explanations in easy-to-understand terms. Plus, you'll see how people are applying genetic science to fight disease, develop new products, solve crimes . . . and even clone cats.
Discover:
What geneticists do How traits are passed on How genetic counseling works The basics of cloning The role of DNA in forensics The scoop on the Human Genome Project
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Bioinformatics and Computational Biology in Drug Discovery and Development
William T. Loging
4.1
Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline.
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BLAST
Ian Korf, Mark Yandell, Joseph Bedell
4.1
Sequence similarity is a powerful tool for discovering biological function. Just as the ancient Greeks used comparative anatomy to understand the human body and linguists used the Rosetta stone to decipher Egyptian hieroglyphs, today we can use comparative sequence analysis to understand genomes. BLAST (Basic Local Alignment Search Tool), is a sophisticated software package for rapid searching of nucleotide and protein databases. It is one of the most important software packages used in sequence analysis and bioinformatics. Most users of BLAST, however, seldom move beyond the program's default parameters, and never take advantage of its full power.
BLAST is the only book completely devoted to this popular suite of tools. It offers biologists, computational biology students, and bioinformatics professionals a clear understanding of BLAST as well as the science it supports. This book shows you how to move beyond the default parameters, get specific answers using BLAST, and how to interpret your results. The book also contains tutorial and reference sections covering NCBI-BLAST and WU-BLAST, background material to help you understand the statistics behind BLAST, Perl scripts to help you prepare your data and analyze your results, and a wealth of tips and tricks for configuring BLAST to meet your own research needs. Some of the topics covered include:
BLAST basics and the NCBI web interface How to select appropriate search parameters BLAST programs: BLASTN, BLASTP, BLASTX, TBLASTN, TBLASTX, PHI-BLAST, and PSI BLAST Detailed BLAST references, including NCBI-BLAST and WU-BLAST Understanding biological sequences Sequence similarity, homology, scoring matrices, scores, and evolution Sequence Alignment Calculating BLAST statistics Industrial-strength BLAST, including developing applications with Perl and BLAST BLAST is the only comprehensive reference with detailed, accurate information on optimizing BLAST searches for high-throughput sequence analysis. This is a book that any biologist should own.
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Antibodies and their role in therapeutics: Monoclonal Antibodies | Immunology | Biotechnology (Biotechnology Books)
Roohi Bansal
4.1
Beginning with the structure, types, functions, and gene organization of antibodies, the book aims to shine a detailed light on the monoclonal antibodies (often referred to as mAbs) that have revolutionized the fields of therapeutics and diagnostics.The book describes the different ways of generating chimeric, humanized, and fully human monoclonal antibodies, emphasizing phage display, hybridoma, and rDNA technology. In addition, the book focuses on the various recombinant antibody formats in detail:Drug conjugates: Antibody-drug conjugates (ADCs), Immunotoxins (Recombinant, Humanized and Fully Human) and Antibody-antibiotic conjugate (AAC)Bispecific antibodies: scFv based (BiTE, DARTs and TandAbs) and Full-length IgG basedAbzymes and Antibody-directed enzyme prodrug therapy (ADEPT)Fc-fusion proteinsSingle-domain antibodies (VHH and IgNAR sdAb)The book discusses the various therapeutic applications of monoclonal antibodies, along with the immunogenicity issues. The book also covers the modes of administration and side effects of monoclonal antibodies, along with the challenges and issues faced while developing a monoclonal antibody into a therapeutic agent. Modifications introduced by the researchers to decrease the immunogenicity issues and increase the efficacy of therapeutic mAbs are also described.The book is an invaluable resource for researchers and students in biology and medicine, biotechnology, immunology, genetics, molecular biology, and anyone interested in antibody engineering.
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Python for Bioinformatics
Jason Kinser
4.1
Bioinformatics is a growing field that attracts researchers from many different backgrounds who are unfamiliar with the algorithms commonly used in the field. Python for Bioinformatics provides a clear introduction to the Python programming language and instructs beginners on the development of simple programming exercises . Ideal for those with some knowledge of computer programming languages, this book emphasizes Python syntax and methodologies. The text is divided into three complete sections; the first provides an explanation of general Python programming, the second includes a detailed discussion of the Python tools typically used in bioinformatics including clustering, associative memories, and mathematical analysis techniques, and the third section demonstrates how these tools are implemented through numerous applications.
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Practical Bioinformatics
Michael Agostino
4.1
Practical Bioinformatics is specifically designed for biology majors, with a heavy emphasis on the steps required to perform bioinformatics analysis to answer biological questions. It is written for courses that have a practical, hands-on element and contains many exercises (for example, database searches, protein analysis, data interpretation) to complement the straightforward and practical topics. The chapters are focused on DNA, RNA, and protein sequence analysis--frequently performed subsets of the field of bioinformatics--taking the reader through the commonly asked question "what can I learn about this sequence?"
A special note to established scientists: new genomic sequences are being published at an accelerating pace. Although new technology has led to unprecedented accuracy of the sequence, incomplete and challenging assemblies along with imperfect predictive methods are still generating gene models that require verification. With the sequence analysis skills learned from this book, features such as missing exons and incorrect termini can be easily recognized and more accurate gene models can be constructed.
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Jira 8 Essentials
Patrick Li
4.1
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Introduction to Protein Structure
Carl Branden, John Tooze
4.1
Introduction to Protein Structure provides an account of the principles of protein structure, with examples of key proteins in their biological context generously illustrated in full-color to illuminate the structural principles described in the text. The first few chapters introduce the general principles of protein structure both for novices and for non-specialists needing a primer. Subsequent chapters use specific examples of proteins to show how they fulfill a wide variety of biological functions. The book ends with chapters on the experimental approach to determining and predicting protein structure, as well as engineering new proteins to modify their functions.
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Computational Biology: A Hypertextbook (ASM Books)
Scott T. Kelley
4.1
An introduction to the world of bioinformatics
Massive increases in computing power and the ability to routinely sequence whole genomes of living organisms have begun to fundamentally alter our understanding of biology, medicine, and agriculture. At the intersection of the growing information and genomics revolutions sits bioinformatics, which uses modern computational power to reveal patterns in biological data sets, especially DNA, RNA, and protein sequences. Computational Biology: A Hypertextbook, by Scott Kelley and Dennis Didulo, provides a wonderful introduction for anyone who wants to learn the basics of bioinformatics. This book is more than a textbook because of the wealth of online ancillary materials and how the print and electronic components are integrated to form a complete educational resource. Aspects that make Computational Biology: A Hypertextbook a unique and valuable tool for teaching and learning bioinformatics include: Clear explanations of the basic biology of DNA, RNA, and proteins and how the related bioinformatics algorithms work; Extensive exercises that enable students to practice with the same bioinformatics applications that are used by scientists worldwide; Tutorials, sample data sets, and interactive learning tools developed with teachers in mind and field-tested by hundreds of students; Online tutorials and curated web links that are accurate (instead of frustrating!) and won’t lead to dead ends; Online resources that work on multiple platforms and electronic devices.
Computational Biology: A Hypertextbook is written in an accessible voice, punctuated with humor, and designed to significantly increase computational competencies. Biology and computer science undergraduate and graduate students will thoroughly enjoy learning from this unique hypertextbook, as will anyone with an interest in exploring this burgeoning topic.
Scott T. Kelley is a professor of biology at San Diego State University. He received his doctoral degree from the University of Colorado and his bachelor’s degree from Cornell University. His lab uses phylogenetic methods and culture-independent molecular tools to study environmental microbiology, and Kelley has published extensively on the human microbiome, built environment, and numerous natural environments. Dennis Didulo is a data analytics and software engineer working at Becton, Dickinson and Company. He received his master’s degree in information technology at De La Salle University and his second master’s degree in bioinformatics at San Diego State University. He has development expertise in more than a dozen computer languages, as well as in database management, algorithm design, and systems engineering.
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R Bioinformatics Cookbook: Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis
Dan MacLean
4.1
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Phylogenetic Trees Made Easy: A How-To Manual (with CD-Rom)
Barry G. Hall
4.1
Phylogenetic Trees Made Easy helps beginners get started in creating phylogenetic trees from protein or nucleic acid sequence data.
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Fundamentals of Biochemistry: Life at the Molecular Level
Donald Voet
4.1
Voet, Voet and Pratt's Fundamentals of Biochemistry, 5e addresses the enormous advances in biochemistry, particularly in the areas of structural biology and Bioinformatics, by providing a solid biochemical foundation that is rooted in chemistry to prepare students for the scientific challenges of the future. While continuing in its tradition of presenting complete and balanced coverage that is clearly written and relevant to human health and disease, Fundamentals of Biochemistry, 5e includes new pedagogy and enhanced visuals that provide a pathway for student learning.
The authors are careful to present new information such that it links it to existing content, ever mindful that students assimilate new information only in the proper context. The enriched assessment content in WileyPLUS Learning Space offers students the opportunity to gauge their conceptual understanding and receive immediate feedback to address misconceptions.
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Bioinformatics: Sequence and Genome Analysis
David Mount
4.1
As more species' genomes are sequenced, computational analysis of these data has become increasingly important. The second, entirely updated edition of this widely praised textbook provides a comprehensive and critical examination of the computational methods needed for analyzing DNA, RNA, and protein data, as well as genomes. The book has been rewritten to make it more accessible to a wider audience, including advanced undergraduate and graduate students. New features include chapter guides and explanatory information panels and glossary terms. New chapters in this second edition cover statistical analysis of sequence alignments, computer programming for bioinformatics, and data management and mining. Practically oriented problems at the ends of chapters enhance the value of the book as a teaching resource. The book also serves as an essential reference for professionals in molecular biology, pharmaceutical, and genome laboratories.
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80
Wetware: A Computer in Every Living Cell
Dennis Bray
4.1
How does a single-cell creature, such as an amoeba, lead such a sophisticated life? How does it hunt living prey, respond to lights, sounds, and smells, and display complex sequences of movements without the benefit of a nervous system? This book offers a startling and original answer.
In clear, jargon-free language, Dennis Bray taps the findings of the new discipline of systems biology to show that the internal chemistry of living cells is a form of computation. Cells are built out of molecular circuits that perform logical operations, as electronic devices do, but with unique properties. Bray argues that the computational juice of cells provides the basis of all the distinctive properties of living systems: it allows organisms to embody in their internal structure an image of the world, and this accounts for their adaptability, responsiveness, and intelligence.
In Wetware, Bray offers imaginative, wide-ranging and perceptive critiques of robotics and complexity theory, as well as many entertaining and telling anecdotes. For the general reader, the practicing scientist, and all others with an interest in the nature of life, the book is an exciting portal to some of biology’s latest discoveries and ideas.
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Introduction to Genomics
Arthur Lesk
4.1
Our genome is the blueprint for our existence: it encodes all the information we need to develop from a single cell into a hugely complicated functional organism. Yet it is more than a static information store: our genome is a dynamic, tightly-regulated collection of genes, which switch on and off in many combinations to give the variety of cells from which our bodies are formed. But how do we identify the genes that make up our genome? How do we determine their function? And how do different genes form the regulatory networks that direct the processes of life?
Introduction to Genomics is the most up-to-date and complete textbook for students approaching the subject for the first time. Lesk's engaging writing style brings a narrative to a disparate field of study and offers a fascinating insight into what can be revealed from the study of genomes. The book covers: the similarities and differences between organisms; how different organisms evolved; how the genome is constructed and how it operates; and what our understanding of genomics means in terms of our future health and wellbeing.
The Online Resource Center accompanying Introduction to Genomics features:
For students *Extensive and imaginative weblems (web-based problems) for each chapter designed to give you practice with the tools required for further study and research in the field *Hints and answers to end-of-chapter problems and exercises support your self-directed learning *Guided tour of websites and major archival databanks in genomics offer a wealth of resources to springboard your own research *Journal club: links to related research articles on topics covered in the book are paired with engaging questions to improve your interpretation of the primary literature *Rotating figures allow you to visualize complex structures
For instructors *Downloadable figures from the book.
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Exploring Bioinformatics: A Project-Based Approach
Caroline St. Clair and Jonathan E. Visick
4.1
Exploring Bioinformatics: A Project-Based Approach Is Intended For An Introductory Course In Bioinformatics At The Undergraduate Level. Through Hands-On Projects, Students Are Introduced To Current Biological Problems And Then Explore And Develop Bioinformatic Solutions To These Issues. Each Chapter Presents A Key Problem, Provides Basic Biological Concepts, Introduces Computational Techniques To Address The Problem, And Guides Students Through The Use Of Existing Web-Based Tools And Existing Software Solutions. This Progression Prepares Students To Tackle The On-Your-Own Project, Where They Develop Their Own Software Solutions. Topics Such As Antibiotic Resistance, Genetic Disease, And Genome Sequencing Provide Context And Relevance To Capture Student Interest.
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Building Ontologies with Basic Formal Ontology
Robert Arp
4.1
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84
Basic Statistics and Epidemiology: A Practical Guide
Antony Stewart
4.1
Basic Statistics and Epidemiology is a straightforward primer in basic statistics that emphasizes its practical use in epidemiology and public health, providing an understanding of essential topics such as study design, data analysis and statistical methods used in the execution of medical research.
Assuming no prior knowledge, the clarity of the text and care of presentation ensure those new to, or challenged by, these topics are given a thorough introduction without being overwhelmed by unnecessary detail. An understanding and appreciation of statistics is central to ensuring that professional practice is based on the best available evidence, in order to treat and help most appropriately the wider community. By reading this book, students, researchers, doctors, nurses and health managers will have the knowledge necessary to understand and apply the tools of statistics and epidemiology to their own practice.
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Python Programming for Biology
Tim J. Stevens and Wayne Boucher
4.1
Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.
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Concepts in Genomics and Bioinformatics
Jamil Momand, Alison McCurdy, et al.
4.0
Concepts in Bioinformatics and Genomics takes a conceptual approach to its subject, balancing biology, mathematics, and programming while highlighting relevant real-world applications and providing students with the tools to compute and analyze biological data. It presents many thought-provoking exercises to stretch students' imaginations, giving them a deeper understanding of the molecular biology, basic probability, software programs, and program-coding methodology underpinning this exciting field.
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Building Bioinformatics Solutions: With Perl, R and MySQL
Conrad Bessant, Ian Shadforth, Darren Oakley
4.0
Modern bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. Building Bioinformatics Solutions provides a comprehensive introduction to this methodology, explaining how to acquire and use the most popular development tools, how to apply them to build processing pipelines, and how to make the results available through visualizations and web-based services for deployment either locally or via the Internet. The main development tools covered in this book are the MySQL database management system, the Perl programming language, and the R language for statistical computing. These industry standard open source tools form the core of many bioinformatics projects, both in academia and industry. The methodologies introduced are platform independent, and all the examples that feature have been tested on Windows, Linux and Mac OS. This advanced textbook is suitable for graduate students and researchers in the life sciences who wish to automate analyses or create their own databases and web-based tools. No prior knowledge of software development is assumed. Having worked through the book, the reader should have the necessary core skills to develop computational solutions for their specific research programmes. The book will also help the reader overcome the inertia associated with penetrating this field, and provide them with the confidence and understanding required to go on to develop more advanced bioinformatics skills.
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Essential MATLAB for Engineers and Scientists
Brian Hahn and Daniel Valentine Ph.D.
4.0
Essential MATLAB for Engineers and Scientists, Seventh Edition, provides a concise, balanced overview of MATLAB's functionality, covering both fundamentals and applications. The essentials are illustrated throughout, featuring complete coverage of the software's windows and menus. Program design and algorithm development are presented, along with many examples from a wide range of familiar scientific and engineering areas. This edition has been updated to include the latest MATLAB versions through 2018b. This is an ideal book for a first course on MATLAB, but is also ideal for an engineering problem-solving course using MATLAB.
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Stat Labs: Mathematical Statistics Through Applications
Deborah Nolan
4.0
Integrating the theory and practice of statistics through a series of case studies, each lab introduces a problem, provides some scientific background, suggests investigations for the data, and provides a summary of the theory used in each case. Aimed at upper-division students.
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Bioinformatics
Andreas D. Baxevanis
4.0
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Principles and Practice of Clinical Research
John I. Gallin
4.0
Principles and Practice of Clinical Research, Fourth Edition has been thoroughly revised to provide a comprehensive look at both the fundamental principles and expanding practice of clinical research. New to this edition of this highly regarded reference, authors have focused on examples that broadly reflect clinical research on a global scale while including a discussion of international regulations, studies, and implications.
In addition to key topics such as bioethics, clinical outcome data, cultural diversity, protocol guidelines, and "omic" platforms, this edition contains new chapters devoted to electronic health records and information resources for clinical researchers, as well as the many opportunities associated with big data. Covering a vast number of topics and practical advice for both novice and advanced clinical investigators, this book is a highly relevant and essential resource for all those involved in conducting research.
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Valuation in Life Sciences: A Practical Guide
Boris Bogdan
4.0
Valuation is a hot topic among life sciences professionals. There is no clear understanding on how to use the different valuation approaches and how to determine input parameters. Some do not value at all, arguing that it is not possible to get realistic and objective numbers out of it. Some claim it to be an art. In the following chapters we will provide the user with a concise val- tion manual, providing transparency and practical insight for all dealing with valuation in life sciences: project and portfolio managers, licensing executives, business developers, technology transfer managers, entrep- neurs, investors, and analysts. The purpose of the book is to explain how to apply discounted cash flow and real options valuation to life sciences p- jects, i.e. to license contracts, patents, and firms. We explain the fun- mentals and the pitfalls with case studies so that the reader is capable of performing the valuations on his own and repeat the theory in the exercises and case studies. The book is structured in five parts: In the first part, the introduction, we discuss the role of the players in the life sciences industry and their p- ticular interests. We describe why valuation is important to them, where they need it, and the current problems to it. The second part deals with the input parameters required for valuation in life sciences, i.e. success rates, costs, peak sales, and timelines.
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93
Genome-Scale Algorithm Design: Biological Sequence Analysis in the Era of High-Throughput Sequencing
Veli Mäkinen, Djamal Belazzougui, Fabio Cunial, Alexandru I. Tomescu
4.0
High-throughput sequencing has revolutionised the field of biological sequence analysis. Its application has enabled researchers to address important biological questions, often for the first time. This book provides an integrated presentation of the fundamental algorithms and data structures that power modern sequence analysis workflows. The topics covered range from the foundations of biological sequence analysis (alignments and hidden Markov models), to classical index structures (k-mer indexes, suffix arrays and suffix trees), Burrows-Wheeler indexes, graph algorithms and a number of advanced omics applications. The chapters feature numerous examples, algorithm visualisations, exercises and problems, each chosen to reflect the steps of large-scale sequencing projects, including read alignment, variant calling, haplotyping, fragment assembly, alignment-free genome comparison, transcript prediction and analysis of metagenomic samples. Each biological problem is accompanied by precise formulations, providing graduate students and researchers in bioinformatics and computer science with a powerful toolkit for the emerging applications of high-throughput sequencing.
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94
Computational Biology: Unix/Linux, Data Processing and Programming
Röbbe Wünschiers
4.0
-Teaches the reader how to use Unix, which is the key to basic computing and allows the most flexibility for bioinformatics applications -Written specifically with the needs of molecular biologists in mind -Easy to follow, written for beginners with no computational knowledge -Includes examples from biological data analysis -Can be use either for self-teaching or in courses
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Sequence Alignment: Methods, Models, Concepts, and Strategies
Michæl S. Rosenberg
4.0
The sequencing of the human genome involved thousands of scientists but used relatively few tools. Today, obtaining sequences is simpler, but aligning the sequences—making sure that sequences from one source are properly compared to those from other sources—remains a complicated but underappreciated aspect of comparative molecular biology. This volume, the first to focus on this crucial step in analyzing sequence data, is about the practice of alignment, the procedures by which alignments are established, and more importantly, how the outcomes of any alignment algorithm should be interpreted. Edited by Michael S. Rosenberg with essays by many of the field's leading experts, Sequence Alignment covers molecular causes, computational advances, approaches for assessing alignment quality, and philosophical underpinnings of the algorithms themselves.
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Cryptography Decrypted
H. X. Mel
4.0
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97
Fundamentals of Neuromechanics
Francisco J. Valero-Cuevas
4.0
This book provides a conceptual and computational framework to study how the nervous system exploits the anatomical properties of limbs to produce mechanical function. The study of the neural control of limbs has historically emphasized the use of optimization to find solutions to the muscle redundancy problem. That is, how does the nervous system select a specific muscle coordination pattern when the many muscles of a limb allow for multiple solutions? I revisit this problem from the emerging perspective of neuromechanics that emphasizes finding and implementing families of feasible solutions, instead of a single and unique optimal solution. Those families of feasible solutions emerge naturally from the interactions among the feasible neural commands, anatomy of the limb, and constraints of the task. Such alternative perspective to the neural control of limb function is not only biologically plausible, but sheds light on the most central tenets and debates in the fields of neural control, robotics, rehabilitation, and brain-body co-evolutionary adaptations. This perspective developed from courses I taught to engineers and life scientists at Cornell University and the University of Southern California, and is made possible by combining fundamental concepts from mechanics, anatomy, mathematics, robotics and neuroscience with advances in the field of computational geometry. Fundamentals of Neuromechanics is intended for neuroscientists, roboticists, engineers, physicians, evolutionary biologists, athletes, and physical and occupational therapists seeking to advance their understanding of neuromechanics. Therefore, the tone is decidedly pedagogical, engaging, integrative, and practical to make it accessible to people coming from a broad spectrum of disciplines. I attempt to tread the line between making the mathematical exposition accessible to life scientists, and convey the wonder and complexity of neuroscience to engineers and computational scientists. While no one approach can hope to definitively resolve the important questions in these related fields, I hope to provide you with the fundamental background and tools to allow you to contribute to the emerging field of neuromechanics.
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98
Genes vs Cultures vs Consciousness: A Brief Story of Our Computational Minds
Andres Campero
4.0
This interdisciplinary scientific short book explores the mind at a conceptual level. It touches on its evolutionary development, its algorithmic nature and its scientific history by bridging ideas across Neuroscience, Computer Science, Biotechnology, Evolutionary History, Cognitive Science, Political Philosophy, and Artificial Intelligence.
Never before had there been nearly as many scientists, resources or productive research focused on these topics, and humanity has achieved some understanding and some clarification. With the speed of progress it is timely to communicate an overreaching perspective, this book puts an emphasis on conveying the essential questions and what we know about their answers in a simple, clear and exciting way.
Humans, along with the first RNA molecules, the first life forms, the first brains, the first conscious animals, the first societies and the first artificial agents constitute an amazing and crucial development in a path of increasingly complex computational intelligence. And yet, we occupy a minuscule time period in the history of Earth, a history that has been written by Genes, by Cultures and by Consciousnesses. If we abandon our anthropomorphic bias it becomes obvious that Humans are not so special after all. We are an important but short and transitory step among many others in a bigger story. The story of our computational minds, which is ours but not only ours.
What is the relationship between computation, cognition and everything else? What is life and how did it originate?
What is the role of culture in human minds? What do we know about the algorithmic nature of the mind, can we engineer it? What is the computational explanation of consciousness?
What are some possible future steps in the evolution of minds? The underlying thread is the computational nature of the Mind which results from the mixture of Genes, Cultures and Consciousness. While these three interact in complex ways, they are ultimately computational systems on their own which appeared at different stages of history and which follow their own selective processes operating at different time scales. As technology progresses, the distinction between the three components materializes and will be a key determinant of the future.
Among the many topics covered are the origin of life, the concept of computation and its relation to Turing Machines, cultural evolution and the notion of a Selfish Meme, free will and determinism, moral relativity, the hard problem of consciousness, the different theories of concepts from the perspective of cognitive science, the current status of AI and Machine Learning including the symbolic vs sub-symbolic dichotomy, the contrast between logical reasoning and neural networks, and the recent history of Deep Learning, Geoffrey Hinton, DeepMind and its algorithm AlphaGo. It also develops on the history of science and looks into the possible future building on the work of authors like Daniel Dennett, Yuval Harari, Richard Dawkins, Francis Crick, George Church, David Chalmers, Susan Carey, Stanislas Dehaene, Robert Boyd, Joseph Henrich, Daniel Kahneman, Moran Cerf, Josh Tenenbaum, David Deutsch, Steven Pinker, Ray Kurzweil, John von Neumann, Herbert Simon and many more.
Andres Campero is a researcher and PhD student at the Brain and Cognitive Sciences Department and at the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (MIT).
Note from the author I think this book is genuinely insightful and fun, and that its story is extremely important. My objective with self-publishing is not to make money, in case that is an issue I am happy to return you the earnings, just contact me at andrescampero.mit.edu. Your purchase would still be helpful for Amazon's search engine: )
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99
Health Information Exchange: Navigating and Managing a Network of Health Information Systems
Brian Dixon
4.0
Health Information Exchange (HIE): Navigating and Managing a Network of Health Information Systems allows health professionals to appropriately access, and securely share, patients' vital medical information electronically, thus improving the speed, quality, safety, and cost of patient care.
The book presents foundational knowledge on HIE, covering the broad areas of technology, governance, and policy, providing a concise, yet in-depth, look at HIE that can be used as a teaching tool for universities, healthcare organizations with a training component, certification institutions, and as a tool for self-study for independent learners who want to know more about HIE when studying for certification exams.
In addition, it not only provides coverage of the technical, policy, and organizational aspects of HIE, but also touches on HIE as a growing profession. In Part One, the book defines HIE, describing it as an emerging profession within HIT/Informatics. In Part Two, the book provides key information on the policy and governance of HIE, including stakeholder engagement, strategic planning, sustainability, etc. Part Three focuses on the technology behind HIE, defining and describing master person indexes, information infrastructure, interfacing, and messaging, etc. In Part Four, the authors discuss the value of HIE, and how to create and measure it. Finally, in Part Five, the book provides perspectives on the future of HIE, including emerging trends, unresolved challenges, etc.
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100
Genomic Perl: From Bioinformatics Basics to Working Code
1
