Bioinformatics: where do I begin?
Matt Brown
Wednesday, 15 August 2007 20:10 UTC
Bioinformatics is an area I feel woefully undereducated in. Can anyone recommend a good book or website (beyond the wikipedia entry) that would give a primer to a scientifically literate, but bioinfomatically illiterate reader?
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Replies
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Hello Matt,
That depends whether you are already familiar with biology, computer science or other areas.
Personally I like the books:
1.”Bioinformatics – Sequence and Genome Analysis” by D. M. Mount
2.”Bioinformatics and Functional Genomics” by J. Pevsner (good for biologists)
3. “Bioinformatics – Genes, Proteins & Computers” by C.A. Orengo, D.T. Jones and J.M. Thornton (good chapters on protein structure/function)Also, I placed some links to bioinformatics educational sites on the web at:
http://bioinfo.bgu.ac.il/bsu/links/index.htm
(at the bottom)
It’s also a good idea to enter and have a look at the databases and software mentioned on this page, and get a feeling on what people develop/use in bioinformatics.I hope this helps, Vered
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Hi Matt,
Good question, and its a difficult one to answer! Bioinformatics really has exploded into a field of everything and anything that relates a computer and a biologist, so, you need to decide which part of the umbrella you wish to stand under!
As a guide, I would agree with Vered, and the third on his list is a book that I am familiar with.
In contrast to that, if you, like me, are more interested in the data analysis/ predictive modelling side of bioinformatics, then i would recomment the book “Microarry bioinformatics” bu Dov Stekel. Although this focuses on microarrays, the approaches are applicable to any source of complex data (eg proteomics).hope this helps, best wishes,
Lee
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Thanks guys, I’ll check some of these things out.
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Bioinformatics.. me too hungry to explore. A mandatory science most of us (especially biologist) want to learn more. can anybody recommed a website that would start from the basics. yes, myself a BIG zero in bioinformatics.. Please guide.
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I have decided to adopt “Understanding Bioinformatics” by Zvelebil & Baum for an introductory course I will be teaching.
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Thanks, Henrik. Hope you will find the book useful. Comments (constructive ones!) will be welcome if we ever do a 2nd edition.
Marketa -
Great topic Matt, I’ll be taking a beginners class in bioinformatics next week (or the week after that). I will write up a couple of posts about it.
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When I started out in bioinformatics – only about 7 years ago – there were almost no books, websites or even university courses. As a consequence, I can’t recommend any because I’ve never looked for them!
What I would say is that bioinformatics is inherently a practical subject – you learn it by doing it. Get comfortable with Linux (or similar) and the command line. Teach yourself a scripting language. Download some of the common free, open-source tools (BLAST, EMBOSS) and try to compile and run them. Grab some example data files from the public databases (NCBI, EBI, PDB) – examine them, understand their format, think about how you could extract useful information from them. Try setting up a web server.
And read bioinformatics blogs.
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On our Masters Bioinformatics course (http://doolittle.ibls.gla.ac.uk/bioinformatics/) we use A Lesk (OUP) as the course text (http://www.oup.com/uk/orc/bin/9780199208043/). This has a reasonably good balance between protein and nucleic aspects of bioinformatics. I haven’t yet seen the third edition, which has just been published.
My own thumbnail definition of bioinformatics from the introduction to our course guide is:
“Bioinformatics is a relatively new subject, although computational biology the application of computational methods to biological problems is not. Bioinformatics certainly stems from computational biology, but the new name does reflect a real change in emphasis following the explosion of available gene and genome sequences in recent years. Whatever its boundaries, the core of bioinformatics is the application of computer methods to the analysis and use of molecular biological information. This involves such things as the analysis of genomes to predict their
protein-coding and other informational potential, deciphering the function of the encoded proteins, analysing and modelling protein structures, deriving evolutionary information from these structures, and using the information in the diagnosis and cure of disease.”
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