Bioinformatics Books!

With the start of 2017 Fall semester, the same standard stream of queries on twitter and linkedin comes along – what are some good reference books for bioinformatics

Now that is indeed a good question. Bioinformatics itself is something that elicits wows from new acquaintances showing complete ignorance at the term. Moreover folks from all sorts of backgrounds have come together to form a bioinformatics world, so to say.

But things are changing, there are 100+ US Universities offering courses in bioinformatics, and scores more online. So that lets us dive into the pivotal aspect of reference books for bioinformatics. A school of thought is that because bioinformatics itself is an ad-hoc mish-mash of everything, going by a book would mean too locked-in and missing out on actual learning. While the lock-in part is true, but with the evolution of bioinformatics over the past decade, there is good reason to have a stable base by following a good book(s). Notice the plural, ehh! As bioinformatics itself is so diverse, there are multiple books one can, and actually should review to master the domain. Here is a listing of what may be called as excellent bioinformatics reference books – these are the classics

Classic #Bioinformatics books

 

  1. Bioinformatics: Sequence and Genome Analysis 2nd (second) by Mount, David (2013) – a must have for anyone starting out, or a keeper for anytime reference
  2. An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) by Neil C. Jones (Author), Pavel A. Pevzner – algorithms are critical in bioinformatics
  3. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids by Richard Durbin, Sean R. Eddy, Anders Krogh Graeme Mitchison

And here are some programing flavored books for bioinformatics experience in Perl, Python, R, Machine Learning, etc.

  1. Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health) by Warren J. Ewens, Gregory R. Grant
  2. Bioinformatics: The Machine Learning Approach, (Adaptive Computation and Machine Learning) by Pierre Baldi, Søren Brunak
  3. Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health). Editors: Gentleman, R., Carey, V., Huber, W., Irizarry, R., Dudoit, S.
  4. Bioinformatics Programming Using Python: Practical Programming for Biological Data by Mitchell L. Model

 

Now some of these books tend to err on the side of being too theoretical. Bioinformatics is a very hands-on field, so try to keep yourself honest in balancing the theoretical knowledge with practical hands-on implementation.

Do share any good reference books that should go in those lists and why some of these or other books are your complete favorites!

 

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