Computer Programming in Quantitative Biology

Computer Programming in Quantitative Biology
Author: R.G. Davies
Publisher: Elsevier
Total Pages: 505
Release: 2012-12-02
Genre: Reference
ISBN: 0323147879
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Computer Programming in Quantitative Biology covers the general background of Fortran coding and the more sophisticated computer programs likely to be encountered in quantitative biology. It discusses the application of over 40 appropriate and easily adaptable programming techniques to problems of major biological interest. Organized into 15 chapters, the book starts by providing an introductory outline of computer structure and function needed to appreciate many basic programming procedures. A chapter discusses some general principles underlying Fortran coding and the use of digital computers, with emphasis on major features of Fortran IV. Other chapters present short introduction to the statistical or mathematical techniques in each of the main sections under which program are described. These chapters also provide some aspects of matrix algebra that are essential for serious statistical programming and offer a general guide to efficiency in programming. All complete programs are accompanied by a flowchart and a detailed discussion. This book is a valuable source of information for biologists, computational biologists, research biologists, undergraduate students, and advanced or specialized students of biology.

Computing for Biologists

Computing for Biologists
Author: Ran Libeskind-Hadas
Publisher: Cambridge University Press
Total Pages: 289
Release: 2014-09-22
Genre: Science
ISBN: 1316061337
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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.

Python Programming for Biology

Python Programming for Biology
Author: Tim J. Stevens
Publisher: Cambridge University Press
Total Pages: 721
Release: 2015-02-12
Genre: Science
ISBN: 1316194140
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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.

A Primer for Computational Biology

A Primer for Computational Biology
Author: Shawn T. O'Neil
Publisher:
Total Pages: 0
Release: 2017-12-21
Genre: Science
ISBN: 9780870719264
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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.

Biological Computation

Biological Computation
Author: Ehud Lamm
Publisher: CRC Press
Total Pages: 332
Release: 2011-05-25
Genre: Mathematics
ISBN: 1420087967
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The area of biologically inspired computing, or biological computation, involves the development of new, biologically based techniques for solving difficult computational problems. A unified overview of computer science ideas inspired by biology, Biological Computation presents the most fundamental and significant concepts in this area. In the book

Quantitative Biology

Quantitative Biology
Author: Akatsuki Kimura
Publisher: Springer
Total Pages: 130
Release: 2022-01-05
Genre: Science
ISBN: 9789811650178
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This textbook is for biologists, to conduct quantitative analysis and modeling of biological processes at molecular and cellular levels. Focusing on practical concepts and techniques for everyday research, this text will enable beginners, both students and established biologists, to take the first step in quantitative biology. It also provides step-by-step tutorials to run various sample programs in one’s personal computer using Excel and Python. This volume traces topics, starting with an introductory chapter, such as modeling, construction and execution of numerical models, and key concepts in quantitative biology: feedback regulations, fluctuations and randomness, and statistical analyses. It also provide sample codes with guidance to procedure programming for actual biological processes such as movement of the nucleus within a cell, cell-cycle regulation, stripe pattern formation of skins, and distribution of energy. Written by a leading research scientist who has a background in biology, studied quantitative approaches by himself, and teaches quantitative biology at several universities, this textbook broadens quantitative approaches for biologists who do not have a strong background in mathematics, physics, or computer programming, and helps them progress further in their research.

Algorithms on Strings, Trees, and Sequences

Algorithms on Strings, Trees, and Sequences
Author: Dan Gusfield
Publisher: Cambridge University Press
Total Pages: 556
Release: 1997-05-28
Genre: Computers
ISBN: 1139811002
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String algorithms are a traditional area of study in computer science. In recent years their importance has grown dramatically with the huge increase of electronically stored text and of molecular sequence data (DNA or protein sequences) produced by various genome projects. This book is a general text on computer algorithms for string processing. In addition to pure computer science, the book contains extensive discussions on biological problems that are cast as string problems, and on methods developed to solve them. It emphasises 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. Its discussion of current algorithms and techniques also makes it a reference for professionals.

Computational Biology

Computational Biology
Author: Röbbe Wünschiers
Publisher: Springer Science & Business Media
Total Pages: 291
Release: 2012-12-06
Genre: Science
ISBN: 3642185525
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-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

Quantitative Biology

Quantitative Biology
Author: Brian Munsky
Publisher: MIT Press
Total Pages: 729
Release: 2018-08-21
Genre: Science
ISBN: 0262347113
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An introduction to the quantitative modeling of biological processes, presenting modeling approaches, methodology, practical algorithms, software tools, and examples of current research. The quantitative modeling of biological processes promises to expand biological research from a science of observation and discovery to one of rigorous prediction and quantitative analysis. The rapidly growing field of quantitative biology seeks to use biology's emerging technological and computational capabilities to model biological processes. This textbook offers an introduction to the theory, methods, and tools of quantitative biology. The book first introduces the foundations of biological modeling, focusing on some of the most widely used formalisms. It then presents essential methodology for model-guided analyses of biological data, covering such methods as network reconstruction, uncertainty quantification, and experimental design; practical algorithms and software packages for modeling biological systems; and specific examples of current quantitative biology research and related specialized methods. Most chapters offer problems, progressing from simple to complex, that test the reader's mastery of such key techniques as deterministic and stochastic simulations and data analysis. Many chapters include snippets of code that can be used to recreate analyses and generate figures related to the text. Examples are presented in the three popular computing languages: Matlab, R, and Python. A variety of online resources supplement the the text. The editors are long-time organizers of the Annual q-bio Summer School, which was founded in 2007. Through the school, the editors have helped to train more than 400 visiting students in Los Alamos, NM, Santa Fe, NM, San Diego, CA, Albuquerque, NM, and Fort Collins, CO. This book is inspired by the school's curricula, and most of the contributors have participated in the school as students, lecturers, or both. Contributors John H. Abel, Roberto Bertolusso, Daniela Besozzi, Michael L. Blinov, Clive G. Bowsher, Fiona A. Chandra, Paolo Cazzaniga, Bryan C. Daniels, Bernie J. Daigle, Jr., Maciej Dobrzynski, Jonathan P. Doye, Brian Drawert, Sean Fancer, Gareth W. Fearnley, Dirk Fey, Zachary Fox, Ramon Grima, Andreas Hellander, Stefan Hellander, David Hofmann, Damian Hernandez, William S. Hlavacek, Jianjun Huang, Tomasz Jetka, Dongya Jia, Mohit Kumar Jolly, Boris N. Kholodenko, Markek Kimmel, Michał Komorowski, Ganhui Lan, Heeseob Lee, Herbert Levine, Leslie M Loew, Jason G. Lomnitz, Ard A. Louis, Grant Lythe, Carmen Molina-París, Ion I. Moraru, Andrew Mugler, Brian Munsky, Joe Natale, Ilya Nemenman, Karol Nienałtowski, Marco S. Nobile, Maria Nowicka, Sarah Olson, Alan S. Perelson, Linda R. Petzold, Sreenivasan Ponnambalam, Arya Pourzanjani, Ruy M. Ribeiro, William Raymond, William Raymond, Herbert M. Sauro, Michael A. Savageau, Abhyudai Singh, James C. Schaff, Boris M. Slepchenko, Thomas R. Sokolowski, Petr Šulc, Andrea Tangherloni, Pieter Rein ten Wolde, Philipp Thomas, Karen Tkach Tuzman, Lev S. Tsimring, Dan Vasilescu, Margaritis Voliotis, Lisa Weber