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A Primer on Python for Life Science Researchers

Authors
Journal
PLoS Computational Biology
1553-734X
Publisher
Public Library of Science
Publication Date
Volume
3
Issue
11
Identifiers
DOI: 10.1371/journal.pcbi.0030199
Keywords
  • Education
  • Computer Science
  • Genetics And Genomics
  • None
Disciplines
  • Biology
  • Computer Science

Abstract

untitled Education A Primer on Python for Life Science Researchers Sebastian Bassi Introduction This article introduces the world of the Pythoncomputer language. It is assumed that readers havesome previous programming experience in at least one computer language and are familiar with basic concepts such as data types, flow control, and functions. Python can be used to solve several problems that research laboratories face almost everyday. Data manipulation, biological data retrieval and parsing, automation, and simulation of biological problems are some of the tasks that can be performed in an effective way with computers and a suitable programming language. The purpose of this tutorial is to provide a bird’s-eye view of the Python language, showing the basics of the language and the capabilities it offers. Main data structures and flow control statements are presented. After these basic concepts, topics such as file access, functions, and modules are covered in more detail. Finally, Biopython, a collection of tools for computational molecular biology, is introduced and its use shown with two scripts. For more advanced topics in Python, there are references at the end. Features of Python Python is a modern programming language developed in the early 1990s by Guido van Rossum [1]. It is a dynamic high- level language with an easily readable syntax. Python programs are interpreted, meaning that there is no need for compilation into a binary form before executing the programs. This makes Python programs a little slower than programs written in a compiled language, but at current computer speeds and for most tasks this is not an issue and the portability that Python gains as a result of being interpreted is a worthwhile tradeoff. The more important and relevant features of Python for our use are that: it is easy to learn, easy to read, interpreted, and multiplatform (Python programs run on most operating systems); it offers free access to source code; internal and external librarie

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