Computing Skills for Biologists: A Toolbox

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

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(s): Stefano Allesina, Madlen Wilmes
Edition: 1
Publisher: Princeton University Press
Year: 2019

Language: English
Commentary: True PDF
Pages: 440
City: Princeton, NJ
Tags: Command Line; Unix; Programming; Debugging; GUI; Data Structures; Python; Bioinformatics; Data Visualization; Relational Databases; R; Statistics; Profiling; NumPy; pandas; LaTeX; SQLite; Programming Style; Data Wrangling; SciPy; Unit Testing; Entry Level; Git; Biopython; Testing; Regular Expressions; Version Control