Computational Biology: A Practical Introduction to BioData Processing and Analysis with Linux, MySQL, and R

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Product Description

This greatly expanded 2nd edition provides a practical introduction to

- data processing with Linux tools and the programming languages AWK and Perl

- data management with the relational database system MySQL, and

- data analysis and visualization with the statistical computing environment R

for students and practitioners in the life sciences. Although written for beginners, experienced researchers in areas involving bioinformatics and computational biology may benefit from numerous tips and tricks that help to process, filter and format large datasets. Learning by doing is the basic concept of this book. Worked examples illustrate how to employ data processing and analysis techniques, e.g. for

- finding proteins potentially causing pathogenicity in bacteria,

- supporting the significance of BLAST with homology modeling, or

- detecting candidate proteins that may be redox-regulated, on the basis of their structure.

All the software tools and datasets used are freely available. One section is devoted to explaining setup and maintenance of Linux as an operating system independent virtual machine. The author's experiences and knowledge gained from working and teaching in both academia and industry constitute the foundation for this practical approach.

Computational Biology: A Practical Introduction to BioData Processing and Analysis with Linux, MySQL, and R Review

I was very glad to find that Dr. R bbe W�nschiers updated and expanded his 2004 book "Computational Biology" in this excellent 2013 second edition. I purchased the first edition about 5 years ago and refer to it from time to time for my computational work. If you need a comprehensive introduction to Computational Biology, I would heartily recommend this book. The writing style is clear and straightforward (although it is sometimes evident that English is not the author's first language but this lends charm to the reading), sometimes with a bit of humor. The author also offers insightful advice along the way, some of which would take you a lot of time and work to put together on your own (at least, it has for me!). The progression from Unix command line/shell scripts to Sed/Awk to Perl pretty much recaps how to logically approach and develop programming skills. Personally, I find Awk especially useful for file manipulation and use it for my data formatting and parsing huge files. Awk can seem arcane at first as it is so concise. Once you get the hang of it, you will find one line of Awk equals 50-80+ lines of Perl or Python for most simple tasks. For more complicated tasks, Dr. W�nschiers includes a chapter on the rudiments of Perl. There are new chapters in the 2nd edition presenting information about Databases and R statistics packages, topics that move the book forward towards dealing with NGS data. The second edition is further strengthened with biologically meaningful exercises. When you master all the aspects presented in the 2nd edition of "Computational Biology", you will be a guru in your own right (and can get paid those big bioinformatic bucks!).

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