A Primer for Computational Biology

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 interd...

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Bibliographic Details
Main Author: O'Neil, Shawn T. (Author)
Format: Electronic eBook
Language:English
Published: Corvallis, Oregon Oregon State University 2017.
Series:Open textbook library.
Subjects:
Online Access:Access online version
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245 0 2 |a A Primer for Computational Biology  |c Shawn O'Neil 
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264 1 |a Corvallis, Oregon  |b Oregon State University  |c 2017. 
264 4 |c ©2017. 
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505 0 |a Part I: Introduction to Unix/Linux -- Part II: Programming in Python -- Part III: Programming in R 
520 0 |a 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. 
542 1 |f Attribution-NonCommercial-ShareAlike 
546 |a In English. 
588 0 |a Description based on print resource 
650 0 |a Computer Science  |v Textbooks 
650 0 |a Biology  |v Textbooks 
700 1 |a O'Neil, Shawn T.  |e author 
710 2 |a Open Textbook Library  |e distributor 
856 4 0 |u https://open.umn.edu/opentextbooks/textbooks/896  |z Access online version