Practical Computing For Biologists

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Practical Computing For Biologists

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Author : Steven H.D. Haddock
language : en
Publisher: Sinauer
Release Date : 2011-04-22

Practical Computing For Biologists written by Steven H.D. Haddock and has been published by Sinauer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-22 with Medical categories.

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.

Computing For Biologists

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Author : Ran Libeskind-Hadas
language : en
Publisher: Cambridge University Press
Release Date : 2014-09-22

Computing For Biologists written by Ran Libeskind-Hadas and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-22 with Science categories.

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

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Author : Tim J. Stevens
language : en
Publisher: Cambridge University Press
Release Date : 2015-02-12

Python Programming For Biology written by Tim J. Stevens and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-12 with Computers categories.

This book introduces Python as a powerful tool for the investigation of problems in computational biology, for novices and experienced programmers alike.

Computing Skills For Biologists

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Author : Stefano Allesina
language : en
Publisher: Princeton University Press
Release Date : 2019-01-15

Computing Skills For Biologists written by Stefano Allesina and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-15 with Computers categories.

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

Bioinformatics Computing

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Author : Bryan P. Bergeron
language : en
Publisher: Prentice Hall Professional
Release Date : 2003

Bioinformatics Computing written by Bryan P. Bergeron and has been published by Prentice Hall Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

Comprehensive and concise, this handbook has chapters on computing visualization, large database designs, advanced pattern matching and other key bioinformatics techniques. It is a practical guide to computing in the growing field of Bioinformatics--the study of how information is represented and transmitted in biological systems, starting at the molecular level.

Developing Bioinformatics Computer Skills

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Author : Cynthia Gibas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2001

Developing Bioinformatics Computer Skills written by Cynthia Gibas and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.

This practical, hands-on guide shows how to develop a structured approach to biological data and the tools needed to analyze it. It's aimed at scientists and students learning computational approaches to biological data, as well as experienced biology researchers starting to use computers to handle data.

Introduction To Scientific Programming With Python

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Author : Joakim Sundnes
language : en
Publisher: Springer Nature
Release Date : 2020-07-01

Introduction To Scientific Programming With Python written by Joakim Sundnes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Mathematics categories.

This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.

Computational Biology

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Author : Röbbe Wünschiers
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Computational Biology written by Röbbe Wünschiers and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.

-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

Analysis Of Biological Data

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Author : Sanghamitra Bandyopadhyay
language : en
Publisher: World Scientific
Release Date : 2007

Analysis Of Biological Data written by Sanghamitra Bandyopadhyay and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, they are scattered in different journals, conference proceedings and technical reports, thus causing inconvenience to readers, students and researchers. This book, unique in its nature, is aimed at providing a treatise in a unified framework, with both theoretical and experimental results, describing the basic principles of soft computing and demonstrating the various ways in which they can be used for analyzing biological data in an efficient manner. Interesting research articles from eminent scientists around the world are brought together in a systematic way such that the reader will be able to understand the issues and challenges in this domain, the existing ways of tackling them, recent trends, and future directions. This book is the first of its kind to bring together two important research areas, soft computing and bioinformatics, in order to demonstrate how the tools and techniques in the former can be used for efficiently solving several problems in the latter. Sample Chapter(s). Chapter 1: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (160 KB). Contents: Overview: Bioinformatics: Mining the Massive Data from High Throughput Genomics Experiments (H Tang & S Kim); An Introduction to Soft Computing (A Konar & S Das); Biological Sequence and Structure Analysis: Reconstructing Phylogenies with Memetic Algorithms and Branch-and-Bound (J E Gallardo et al.); Classification of RNA Sequences with Support Vector Machines (J T L Wang & X Wu); Beyond String Algorithms: Protein Sequence Analysis Using Wavelet Transforms (A Krishnan & K-B Li); Filtering Protein Surface Motifs Using Negative Instances of Active Sites Candidates (N L Shrestha & T Ohkawa); Distill: A Machine Learning Approach to Ab Initio Protein Structure Prediction (G Pollastri et al.); In Silico Design of Ligands Using Properties of Target Active Sites (S Bandyopadhyay et al.); Gene Expression and Microarray Data Analysis: Inferring Regulations in a Genomic Network from Gene Expression Profiles (N Noman & H Iba); A Reliable Classification of Gene Clusters for Cancer Samples Using a Hybrid Multi-Objective Evolutionary Procedure (K Deb et al.); Feature Selection for Cancer Classification Using Ant Colony Optimization and Support Vector Machines (A Gupta et al.); Sophisticated Methods for Cancer Classification Using Microarray Data (S-B Cho & H-S Park); Multiobjective Evolutionary Approach to Fuzzy Clustering of Microarray Data (A Mukhopadhyay et al.). Readership: Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, artificial intelligence, data mining, machine learning, electrical engineering, system science; researchers in pharmaceutical industries.