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Author : Tim J. Stevens,Wayne Boucher
Publisher : Cambridge University Press
Page : 721 pages
File Size : 52,6 Mb
Release : 2015-02-12
Category : Science
ISBN : 9780521895835
This book introduces Python as a powerful tool for the investigation of problems in computational biology, for novices and experienced programmers alike.
Author : Martin Jones
Publisher : Createspace Independent Publishing Platform
Page : 248 pages
File Size : 53,6 Mb
Release : 2013
Category : Biology
ISBN : UCR:31210023746751
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.
Author : Ran Libeskind-Hadas,Eliot Bush
Publisher : Cambridge University Press
Page : 128 pages
File Size : 42,5 Mb
Release : 2014-09-22
Category : Science
ISBN : 9781316061336
Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.
Author : Mitchell L Model
Publisher : "O'Reilly Media, Inc."
Page : 526 pages
File Size : 41,5 Mb
Release : 2009-12-08
Category : Science
ISBN : 9781449382902
Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks. Become familiar with Python's fundamentals, including ways to develop simple applications Learn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database access Discover generalized patterns that cover a large proportion of how Python code is used in bioinformatics Learn how to apply the principles and techniques of object-oriented programming Benefit from the "tips and traps" section in each chapter
Author : Yasha Hasija,Rajkumar Chakraborty
Publisher : CRC Press
Page : 243 pages
File Size : 44,6 Mb
Release : 2021-04-09
Category : Science
ISBN : 9781000345506
Hands-on Data Science for Biologists using Python has been conceptualized to address the massive data handling needs of modern-day biologists. With the advent of high throughput technologies and consequent availability of omics data, biological science has become a data-intensive field. This hands-on textbook has been written with the inception of easing data analysis by providing an interactive, problem-based instructional approach in Python programming language. The book starts with an introduction to Python and steadily delves into scrupulous techniques of data handling, preprocessing, and visualization. The book concludes with machine learning algorithms and their applications in biological data science. Each topic has an intuitive explanation of concepts and is accompanied with biological examples. Features of this book: The book contains standard templates for data analysis using Python, suitable for beginners as well as advanced learners. This book shows working implementations of data handling and machine learning algorithms using real-life biological datasets and problems, such as gene expression analysis; disease prediction; image recognition; SNP association with phenotypes and diseases. Considering the importance of visualization for data interpretation, especially in biological systems, there is a dedicated chapter for the ease of data visualization and plotting. Every chapter is designed to be interactive and is accompanied with Jupyter notebook to prompt readers to practice in their local systems. Other avant-garde component of the book is the inclusion of a machine learning project, wherein various machine learning algorithms are applied for the identification of genes associated with age-related disorders. A systematic understanding of data analysis steps has always been an important element for biological research. This book is a readily accessible resource that can be used as a handbook for data analysis, as well as a platter of standard code templates for building models.
Author : Shawn T. O'Neil
Publisher : Unknown
Page : 0 pages
File Size : 40,6 Mb
Release : 2017-12-21
Category : Science
ISBN : 0870719262
A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the "natural environment" of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful "pipe" operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.
Author : Allegra Via,Kristian Rother,Anna Tramontano
Publisher : CRC Press
Page : 560 pages
File Size : 45,8 Mb
Release : 2014-03-18
Category : Computers
ISBN : 9781439880944
Take Control of Your Data and Use Python with ConfidenceRequiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how
Author : Alexander Lancaster,Gordon Webster
Publisher : Apress
Page : 396 pages
File Size : 45,6 Mb
Release : 2019-09-27
Category : Computers
ISBN : 9781484245231
Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you. What You'll Learn Write Python scripts to automate your lab calculations Search for important motifs in genome sequences Use object-oriented programming with Python Study mining interaction network data for patterns Review dynamic modeling of biochemical switches Who This Book Is For Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers. “A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective” -- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow “Fun, entertaining, witty and darn useful. A magical portal to the big data revolution” -- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School “Alex and Gordon’s enthusiasm for Python is contagious” -- Glenys Thomson Professor of Integrative Biology, University of California, Berkeley
Author : Sebastian Bassi
Publisher : CRC Press
Page : 510 pages
File Size : 53,9 Mb
Release : 2017-08-07
Category : Mathematics
ISBN : 9781351976954
In today's data driven biology, programming knowledge is essential in turning ideas into testable hypothesis. Based on the author’s extensive experience, Python for Bioinformatics, Second Edition helps biologists get to grips with the basics of software development. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language. This new edition is updated throughout to Python 3 and is designed not just to help scientists master the basics, but to do more in less time and in a reproducible way. New developments added in this edition include NoSQL databases, the Anaconda Python distribution, graphical libraries like Bokeh, and the use of Github for collaborative development.
Author : Stefano Allesina,Madlen Wilmes
Publisher : Princeton University Press
Page : 440 pages
File Size : 55,6 Mb
Release : 2019-01-15
Category : Computers
ISBN : 9780691182759
A concise introduction to key computing skills for biologists While biological data continues to grow exponentially in size and quality, many of today’s biologists are not trained adequately in the computing skills necessary for leveraging this information deluge. In Computing Skills for Biologists, Stefano Allesina and Madlen Wilmes present a valuable toolbox for the effective analysis of biological data. Based on the authors’ experiences teaching scientific computing at the University of Chicago, this textbook emphasizes the automation of repetitive tasks and the construction of pipelines for data organization, analysis, visualization, and publication. Stressing practice rather than theory, the book’s examples and exercises are drawn from actual biological data and solve cogent problems spanning the entire breadth of biological disciplines, including ecology, genetics, microbiology, and molecular biology. Beginners will benefit from the many examples explained step-by-step, while more seasoned researchers will learn how to combine tools to make biological data analysis robust and reproducible. The book uses free software and code that can be run on any platform. Computing Skills for Biologists is ideal for scientists wanting to improve their technical skills and instructors looking to teach the main computing tools essential for biology research in the twenty-first century. Excellent resource for acquiring comprehensive computing skills Both novice and experienced scientists will increase efficiency by building automated and reproducible pipelines for biological data analysis Code examples based on published data spanning the breadth of biological disciplines Detailed solutions provided for exercises in each chapter Extensive companion website
Author : Ran Libeskind-Hadas,Eliot Christen Bush
Publisher : Unknown
Page : 220 pages
File Size : 47,7 Mb
Release : 2014
Category : Biology
ISBN : 1316054233
Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.
Author : Ken Youens-Clark
Publisher : "O'Reilly Media, Inc."
Page : 457 pages
File Size : 55,8 Mb
Release : 2021-05-05
Category : Computers
ISBN : 9781098100858
Life scientists today urgently need training in bioinformatics skills. Too many bioinformatics programs are poorly written and barely maintained--usually by students and researchers who've never learned basic programming skills. This practical guide shows postdoc bioinformatics professionals and students how to exploit the best parts of Python to solve problems in biology while creating documented, tested, reproducible software. Ken Youens-Clark, author of Tiny Python Projects (Manning), demonstrates not only how to write effective Python code but also how to use tests to write and refactor scientific programs. You'll learn the latest Python features and toolsâ??including linters, formatters, type checkers, and testsâ??to create documented and tested programs. You'll also tackle 14 challenges in Rosalind, a problem-solving platform for learning bioinformatics and programming. Create command-line Python programs to document and validate parameters Write tests to verify refactor programs and confirm they're correct Address bioinformatics ideas using Python data structures and modules such as Biopython Create reproducible shortcuts and workflows using makefiles Parse essential bioinformatics file formats such as FASTA and FASTQ Find patterns of text using regular expressions Use higher-order functions in Python like filter(), map(), and reduce()
Author : Steven H.D. Haddock,Casey W. Dunn
Publisher : Sinauer
Page : 0 pages
File Size : 50,9 Mb
Release : 2011-04-22
Category : Medical
ISBN : 0878933913
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. Many of the techniques are relevant to molecular bioinformatics but the scope of the book is much broader, covering topics and techniques that are applicable to a range of scientific endeavours. Twenty-two chapters organized into six parts address the following 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 the main narrative focuses on Mac OS X, most of the concepts and examples apply to any operating system. 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.
Author : Hans Petter Langtangen
Publisher : Springer
Page : 942 pages
File Size : 48,9 Mb
Release : 2016-07-28
Category : Computers
ISBN : 9783662498873
The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015
Author : Tim J. Stevens,Wayne Boucher
Publisher : Cambridge University Press
Page : 721 pages
File Size : 42,7 Mb
Release : 2015-02-12
Category : Science
ISBN : 9781316194140
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.