Python for Bioinformatics

Sebastian Bassi

September 30, 2009 by Chapman and Hall/CRC
Reference - 587 Pages - 54 B/W Illustrations
ISBN 9781584889298 - CAT# C9292
Series: Chapman & Hall/CRC Mathematical and Computational Biology

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  • Provides a solid introduction to programming with Python, making the book accessible for readers without previous programming experience
  • Covers advanced topics, such as XML, CGI, WSGI, version control, and databases
  • Contains ready-to-use working code that solves real-world biological problems
  • Includes a DVD with a ready-to-run virtual machine based in DNALinux to test the code and offers installation instructions in an appendix


Programming knowledge is often necessary for finding a solution to a biological problem. Based on the author’s experience working for an agricultural biotechnology company, Python for Bioinformatics helps scientists solve their biological problems by helping them understand the basics of programming. Requiring no prior knowledge of programming-related concepts, the book focuses on the easy-to-use, yet powerful, Python computer language.

The book begins with a very basic introduction that teaches the principles of programming. It then introduces the Biopython package, which can be useful in solving life science problems. The next section covers sophisticated tools for bioinformatics, including relational database management systems and XML. The last part illustrates applications with source code, such as sequence manipulation, filtering vector contamination, calculating DNA melting temperature, parsing a genbank file, inferring splicing sites, and more. The appendices provide a wealth of supplementary information, including instructions for installing Python and Biopython and a Python language and style guide.

By incorporating examples in biology as well as code fragments throughout, the author places a special emphasis on practice, encouraging readers to experiment with the code. He shows how to use Python and the Biopython package for building web applications, genomic annotation, data manipulation, and countless other applications.