A Primer for Computational Biology
Download Full Text
Shawn T. O'Neil - Author
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.
Natural Sciences - Biology
Oregon State University
Open Textbook Library
"A Primer for Computational Biology" (2021). Open Access Textbooks. 779.