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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:
Part I, 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.
Part II, 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.
Part III, 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.
Shawn T. O’Neil earned a BS in computer science from Northern Michigan University, and later an MS and PhD in the same subject from the University of Notre Dame. His past and current research focuses on bioinformatics. O’Neil has developed and taught several courses in computational biology at both Notre Dame and Oregon State University.