Best Bioinformatics Books
Here you will get Best Bioinformatics Books For you.This is an up-to-date list of recommended books.
1. System Design Interview – An insider's guide, Second Edition
Author: by Alex Xu
B08CMF2CQF
English
322 pages
The system design interview is considered to be the most complex and most difficult technical job interview by many. This book provides a step-by-step framework on how to tackle a system design question. It includes many real-world examples to illustrate the systematic approach with detailed steps that you can follow.What’s inside?
An insider’s take on what interviewers really look for and why. A 4-step framework for solving any system design interview question. 16 real system design interview questions with detailed solutions. 188 diagrams to visually explain how different systems work. Table Of Contents Chapter 1: Scale From Zero To Millions Of Users Chapter 2: Back-of-the-envelope Estimation Chapter 3: A Framework For System Design Interviews Chapter 4: Design A Rate Limiter Chapter 5: Design Consistent Hashing Chapter 6: Design A Key-value Store Chapter 7: Design A Unique Id Generator In Distributed Systems Chapter 8: Design A Url Shortener Chapter 9: Design A Web Crawler Chapter 10: Design A Notification System Chapter 11: Design A News Feed System Chapter 12: Design A Chat System Chapter 13: Design A Search Autocomplete System Chapter 14: Design Youtube Chapter 15: Design Google Drive Chapter 16: The Learning Continues
2. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
Author: by Trevor Hastie
Springer
English
767 pages
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing 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 colour 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 factorisation, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates.
3. Pattern Recognition and Machine Learning (Information Science and Statistics)
Author: by Christopher M. Bishop
Springer (August 17, 2006)
English
738 pages
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning.
No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
4. Fundamentals of Biochemistry: Life at the Molecular Level
Author: by Donald Voet
Wiley
English
1184 pages
NOTE: Access Code NOT INCLUDED Voet, Voet and Pratt’s Fundamentals of Biochemistry, 5th Edition 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.
5. Biostatistics For Dummies
Author: by John Pezzullo
For Dummies
English
408 pages
Score your highest in biostatistics Biostatistics is a required course for students of medicine, epidemiology, forestry, agriculture, bioinformatics, and public health. In years past this course has been mainly a graduate-level requirement; however its application is growing and course offerings at the undergraduate level are exploding.
Biostatistics For Dummies is an excellent resource for those taking a course, as well as for those in need of a handy reference to this complex material. Biostatisticiansanalysts of biological dataare charged with finding answers to some of the world’s most pressing health questions: how safe or effective are drugs hitting the market today?What causes autism?
What are the risk factors for cardiovascular disease? Are those risk factors different for men and women or different ethnic groups? Biostatistics For Dummies examines these and other questions associated with the study of biostatistics. Provides plain-English explanations of techniques and clinical examples to help Serves as an excellent course supplement for those struggling with the complexities of the biostatistics Tracks to a typical, introductory biostatistics course Biostatistics For Dummies is an excellent resource for anyone looking to succeed in this difficult course.
6. An Introduction to Systems Biology: Design Principles of Biological Circuits (Chapman & Hall/CRC Computational Biology Series)
Author: by Uri Alon
Chapman and Hall/CRC
English
342 pages
Praise for the first edition: superb, beautifully written and organized work that takes an engineering approach to systems biology. Alon provides nicely written appendices to explain the basic mathematical and biological concepts clearly and succinctly without interfering with the main text.
He starts with a mathematical description of transcriptional activation and then describes some basic transcription-network motifs (patterns) that can be combined to form larger networks. Nature [This text deserves] serious attention from any quantitative scientist who hopes to learn about modern biology It assumes no prior knowledge of or even interest in biology One final aspect that must be mentioned is the wonderful set of exercises that accompany each chapter.
Alon’s book should become a standard part of the training of graduate students. Physics Today Written for students and researchers, 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 systems.
7. Who We Are and How We Got Here: Ancient DNA and the new science of the human past
Author: by David Reich
English
368 pages
0198821263
The past few years have seen a revolution in our ability to map whole genome DNA from ancient humans. With the ancient DNA revolution, combined with rapid genome mapping of present human populations, has come remarkable insights into our past.
This important new data has clarified and added to our knowledge from archaeology and anthropology, helped resolve long-existing controversies, challenged long-held views, and thrown up some remarkable surprises. The emerging picture is one of many waves of ancient human migrations, so that all populations existing today are mixes of ancient ones, as well as in many cases carrying a genetic component from Neanderthals, and, in some populations, Denisovans.
David Reich, whose team has been at the forefront of these discoveries, explains what the genetics is telling us about ourselves and our complex and often surprising ancestry. Gone are old ideas of any kind of racial ‘purity’, or even deep and ancient divides between peoples.
Instead, we are finding a rich variety of mixtures. Reich describes the cutting-edge findings from the past few years, and also considers the sensitivities involved in tracing ancestry, with science sometimes jostling with politics and tradition. He brings an important wider message: that we should celebrate our rich diversity, and recognize that every one of us is the result of a long history of migration and intermixing of ancient peoples, which we carry as ghosts in our DNA.
8. BIOINFORMATICS ALGORITHMS
Author: by Phillip Compeau
Active Learning Publishers
English
728 pages
This is the third edition of Bioinformatics Algorithms: an Active Learning Approach, one of the first textbooks to emerge from the revolution in online learning. A light hearted and analogy filled companion to the authors’ acclaimed online courses, 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 students of both biology and computer science. Each chapter begins with a 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, a popular platform for learning bioinformatics through programming.
9. Bioinformatics and Functional Genomics
Author: by Jonathan Pevsner
Wiley-Blackwell
English
1160 pages
The bestselling introduction to bioinformatics and genomics now in its third editionWidely received in its previous editions, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline. Now in a thoroughly updated and expanded third edition, it continues to be the go-to source for students and professionals involved in biomedical research.
This book provides up-to-the-minute coverage of the fields of bioinformatics and genomics. Features new to this edition include: Extensive revisions and a slight reorder of chapters for a more effective organization A brand new chapter on next-generation sequencing An expanded companion website, also updated as and when new information becomes available Greater emphasis on a computational approach, with clear guidance of how software tools work and introductions to the use of command-line tools such as software for next-generation sequence analysis, the R programming language, and NCBI search utilities The book is complemented by lavish illustrations and more than 500 figures and tables – many newly-created for the third edition to enhance clarity and understanding.
10. R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics
Author: by JD Long
O'Reilly Media
English
600 pages
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately.
Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started.
If you’re an intermediate user, this book 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 basic functionsSimplify data input and outputTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your data
11. Learning R: A Step-by-Step Function Guide to Data Analysis
Author: by Richard Cotton
O'Reilly Media
English
400 pages
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 doUse data types such as vectors, arrays, lists, data frames, and stringsExecute code conditionally or repeatedly with branches and loopsApply R add-on packages, and package your own work for othersLearn how to clean data you import from a variety of sourcesUnderstand data through visualization and summary statisticsUse statistical models to pass quantitative judgments about data and make predictionsLearn what to do when things go wrong while writing data analysis code
12. Pattern Recognition and Machine Learning (Information Science and Statistics)
Author: by Christopher M. Bishop
Springer
English
758 pages
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning.
No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
13. MATLAB: A Practical Introduction to Programming and Problem Solving
Author: by Dorothy C. Attaway Ph.D. Boston University
Butterworth-Heinemann
English
626 pages
MATLAB: A Practical Introduction to Programming and Problem Solving, winner of TAA’s 2017 Textbook Excellence Award (“Texty”), guides the reader through both programming and built-in functions to easily exploit MATLAB’s extensive capabilities for tackling engineering and scientific problems. Assuming no knowledge of programming, this 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.
The fifth edition has been updated to reflect the functionality of the current version of MATLAB (R2018a), including the addition of local functions in scripts, the new string type, coverage of recently introduced functions to import data from web sites, and updates to the Live Editor and App Designer.
14. Clinical Informatics Board Review and Self Assessment
Author: by Scott Mankowitz
Springer
English
355 pages
The book offers an introduction to all the informatics concepts that are represented on the Clinical Informatics Board Examination The core and direction of this book is to mirror the model of clinical informatics which is used by the American Board of Preventive Medicine to create their exam.
Unlike any other text on the market, the book includes simulated exam questions, to help the reader asses his knowledge and focus his study. Clinical Informatics Board Review and Self Assessment is a thorough practical assistant to refine the reader’s knowledge regarding this youngest and possibly broadest fields of medicine.
15. Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools
Author: by Vince Buffalo
O'Reilly Media
English
538 pages
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 scripting languages like Python 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
16. Biomedical Informatics: Computer Applications in Health Care and Biomedicine
Author: by Edward H. Shortliffe
Springer
English
1195 pages
This 5th edition of this essential textbook continues to meet the growing demand of practitioners, researchers, educators, and students for a comprehensive introduction to key topics in biomedical informatics and the underlying scientific issues that sit at the intersection of biomedical science, patient care, public health and information technology (IT).
Emphasizing the conceptual basis of the field rather than technical details, it provides the tools for study required for readers to comprehend, assess, and utilize biomedical informatics and health IT. It focuses on practical examples, a guide to additional literature, chapter summaries and a comprehensive glossary with concise definitions of recurring terms for self-study or classroom use.
Biomedical Informatics: Computer Applications in Health Care and Biomedicine reflects the remarkable changes in both computing and health care that continue to occur and the exploding interest in the role that IT must play in care coordination and the melding of genomics with innovations in clinical practice and treatment.
