I am looking for personal experiences and short opinions regarding bioinformatics books.

So far I have noticed the following trend: many books titled Bioinformatics with Perl/Python/Java/R etc end up being introductions into the programming language in question, often only minor code examples are related to bioinformatics.

Help us find some good books!

PS. If you are willing to write a standalone book review is even better. Please do so by creating a new question titled: "Book review for X" then answer it with your own review.

I would like to recommend the following books to any one who is interested in Bioinformatics (Not in order):

1. Genes, Proteins and Computers : A concise introduction to the subject, mainly from a biological view point, yet provide a solid understanding of fundamental concepts in biology, computing, algorithm and statistics related to bioinformatics. Must read.
2. Bioinformatics by David Mount : A very detailed account of bioinformatics concepts. I think its high time to revise this book. I am looking forward for the next edition. You should have a copy of this if you are Masters' or PhD in Bioinformatics.
3. Bioinformatics : Unix/Linux, Data Processing and Programming : This is a cute little book that gives you an edge over Unix, linux, basic data processing and little bit of Perl programming. I appreciate this book for its handy examples. Highly recommend to those who are from biology and interest to get their hands on programming.
4. Bioinformatics : Machine learning approaches Machine learning is now an integral part of bioinformatics and bioinformatics is an emerging area for the application of machine learning techniques. For computer science students : here is the real dose of bioinformatics algorithms. One of the first authentic books on bioinformatics algorithms.
5. An Introduction to Bioinformatics Algorithms This one is my favorite, especially the pseudocode section and classification of algorithms and its concise description. Book features extensive content on the algorithms used in bioinforamtics categorized into different groups with interesting cartoons. A unique concept introduced in the book is profile of the authors. If you are really in to bioinformatics algorithms, this should be on your desk.

PS. I have couple of more like Computational Genome Analysis, Programming Collective Intelligence etc. But they are more of specialized in to different sub-domains of bioinformatics.

I really like Biological Sequence Analysis, Durbin et al. and, although not really bioinformatics-specific, I found Perl Medic, Peter J. Scott made a big difference to my newbie Perl code. For biology text books, I mainly relied on Lewin and Alberts for background during my undergrad.

I've been doing bioinformatics for 10 years or so and have never read a book on the subject. I learned (and still learn, every day) on the job, almost entirely from online resources.

I think many bioinformaticians of a "certain age" learned in this way: they are often former bench biologists who gave up lab work and taught themselves programming. These days there are undergraduate courses (!), so I imagine more people use textbooks. It's just that I don't know of any, nor have I ever needed to use one.

Most of my sparse experience with bioinformatics came with the necessity to extract some statistics from sequence data. So, most books I can recommend deal with statistical and algorithmic approaches to biological data.

• An Introduction to Bioinformatics Algorithms Neil C. Jones and Pavel A. Pevzner

• Statistical Methods in Bioinformatics Warren J. Ewens, Gregory R. Grant

• Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison David Sankoff, Joseph Kruskal

• Bioinformatics and Computational Biology Solutions Using R and Bioconductor Robert Gentleman, Vincent Carey, Wolfgang Huber, Rafael Irizarry, Sandrine Dudoit

Jones and Pavel are accomplished mathematicians and bioinformaticians. Their work with repeats is a must have reference. Ewens's book will become a classic. He is already a foremost figure in population genetics, both in theory and experiment. Sankoff's book still is the most important reference in sequence aligment. Unfortunatelly, these books are somewhat mind bending. They rely heavily on mathematical concepts. But, as far as I know, bioinformatics theory is indeed mathematically and algorithmically challenging.

And the last book is a very broad practical introduction to bioinformatics of array data. Good for relaxing . . .

Cheers !

Ok well I think I will just stick to R for now. I do some work with BioConductor and have the following texts on my desk:

Bioinformatics and Computational Biology Solutions Using R and Bioconductor (http://www.bioconductor.org/docs/mogr/) is a good text to get to grips with common data processing tasks for microarray and proteomics analysis which covers QC, normalisation, one and two colour array data, and downstream data analysis. It needs an update, some of the example code does not work with more modern BioConductor releases but it is still a useful resource.

Bioconductor Case Studies (http://www.bioconductor.org/pub/biocases/) focuses less on the specifics of the packages and more on the workflows of common bioinformatics analyses, including GSEA, machine learning, pulling data from remote resources, statistical modelling and visualisation. It also benefits from being a more recent release than it's counterpart above.

Neither of these books will teach you R however. My general R programming reference is:

R Programming for Bioinformatics (http://www.bioconductor.org/pub/RBioinf/) which tells you more about R than you probably ever want to (or care) to know. Whilst it is aimed at a bioinformatics audience it does not skip it's role as a text primarily to teach you how to program in R.

If youre looking for a tome that brings your statistics up to speed instead within the R framework then I have long had a copy of Introductory Statistics With R (http://www.amazon.co.uk/dp/0387790535/?tag=sollc-gb-20) it's not a long book by any means but will get you used to handling data and applying statistical tests in R.

I've never found a good bioinformatics book.

All the books I've glanced :

• were too much theoretical
• were too much trivial
• don't have enough examples (code...)
• only used perl
• ...

at the end, I learned much more at reading the blogs and the IT sites.

Durbin, R. et al. (1998). Biological sequence analysis: probabilistic models of proteins and nucleic acids. Cambridge University Press.

A few have mentioned this book, but I would still like to emphasize it more in a separate answer. This book covers a lot of topics and on each topic it gives very comprehensive and in-depth review. After 10 years, I still benefit from this book, finding meticulous but invaluable details I have overlooked. This is exceptional among general textbooks on bioinformatics. Some may argue the book is too old, but interestingly, when you read the book, you will find that there are not so many breakthroughs in Bioinformatics in the past 12 years -- many old techniques are still useful till now.

There are other excellent textbooks in subfields. The ones I have read and think are worth buying are:

• Nei and Kumar, Molecular evolution and phylogenetics (for phylogenetics)
• Hein et al, Gene genealogies, variation and evolution (for coalescent theory)

Again, I benefit these books for years, not just the time I was reading them.

I almost never systematically read a book on programming or programming languages. As others have suggested, for these things, the best way is to practice and learn from the web.

I'll tell an acedote about the book that introduced me to bioinformatics.

Let me preface that I have three big interests in my life: biology, computer science and sailing. The year was around 2000, and I had found the book The New New Thing : A Silicon Valley Story by Michael M. Lewis. It was about two of my interests: computer science and sailing.

It is the biography of Jim Clark, a technology entrepreneur who is about to create his third, separate, billion-dollar company: first Silicon Graphics, then Netscape--and now Healtheon, a startup which he hopes will turn the $1 trillion healthcare industry on its head. But after coming up with the basic idea for Healtheon, securing the initial seed money, and hiring the people to make it happen, Clark concentrated on the building of Hyperion, a sailboat with a 197-foot mast (at the time of her launch, she was the largest sloop ever build and the tallest mast ever built), whose functions are controlled by 25 SGI workstations. As the title implies, Jim Clark is a restless man who was always looking for the new new thing, the next big breaktrough. Near the end of the book Michael Lewis tells about one of the new things of Jim Clarks radar, a new emerging field called bioinformatics.

I remember sitting there in my chair, staring at that sentence and thinking "What! I can combine both biology and computer science!" From that moment on I was hooked.

(The book with the ultimate triumvirate, where the three of my interest -biology, computer science and sailing- were combined, came later with the autobiography of Craig Venter, A life decoded, where he writes about the Global Ocean Sampling Expedition he undertook with his personal 95-foot sailboat named the Sorcerer II. The expedition sampled water from Halifax, Nova Scotia to the Eastern Tropical Pacific while undertaking a two year circumnavigation. The micro-organisms in the water were sequenced and the results were published, more then doubling the amount of genetic sequences available up to that point.)

I think you are spot on with your observation. For some reason most of the recent bioinformatics books, particularly the expensive hardcover ones from CRC and Springer, are written by non-practitioners. By non-practitioners I mean professors who teach statistics, biological science or computer science, as opposed to software developers working in the field of bioinformatics. The result has read like a cross-section of stodgy textbooks and research articles, with little in the way of practical code or analysis strategy. Others, as you mention, are "mildly bio-flavored" introductions to a programming language. I love technical books but with a couple exceptions (Beginning Perl for Bioinformatics) I have never felt bioinformatics books were worth the money.

I am looking forward to reading Bioinformatics Programming Using Python. I think it will be a good one.

My reviews:

• Statistical Bioinformatics: with R
• A Primer of Genome Science, Third Edition,
• R Programming for Bioinformatics

It hasn't been mentioned yet but Algorithms on Strings, Tree's and Sequences is a fantastic book if you are looking to learn about sequence alignment.

I've learnt pretty much everything from doing, i.e. programming, and rely heavily on online resources. There have been occasional programming books that I've used to bootstrap learning about a language (especially if it was a major leap, say from procedural to object-oriented languages, or from standalone application programming to web scripting). Of the bioinformatics books mentioned so far, Durbin et al., Biological Sequence Analysis was the book I got the most out of, especially the section on RNA secondary structure, which I was obsessed with for a time. Good description of the problem, algorithms clearly explained, and pseudocode. Great stuff.

Perhaps off topic, but the books I find most fun and inspiring to read have been more general web-oriented books such as Ambient Findability: What We Find Changes Who We Become .

Some of the textbooks I have found useful for research, lecturing and project supervision in bioinformatics are:

1. Bioinformatics: Sequence and Genome Analysis by Mount - useful for organizing graduate/undergraduate lectures and introducing students to concepts in classical sequence analysis, limited code examples.
2. Essential Bioinformatics by Xiong - overview of classical bioinformatics, useful for organizing undergraduate lectures, no code examples.
3. Introduction to Bioinformatics by Lesk - overview of biological context, classical sequence analysis and 'omics, useful for lecture material but somewhat incomplete, no code examples.
4. Understanding Bioinformatics by Zvelebil and Baum - more up-to-date general overview of bioinformatics, including some basic biology concepts, good for computer scientists coming to bioinformatics, no code examples.
5. Bioinformatics for Dummies by Claverie and Notredame - good intro of concepts, jargon and classical web resources in bioinformatics, good for project students and computer scientists coming to bioinformatics, no code examples.
6. Biological Sequence Analysis by Durbin, Eddy, Krough and Mitchison - excellent treatment of probabalistic methods in bioinformatics including HMMs, pseduocode of algorithms provided (see also the companion Problems and Solutions in Biological Sequence Analysis by Borodovsky and Ekisheva for example problems useful in teaching).
7. PostgreSQL by Momjian - excellent introduction to basic SQL concepts, many code examples.
8. XML for Bioinformatics by Cerami - very good introduction to XML in a bioinformatics context, good code examples.
9. Molecular Evolution by Li - essential introduction to molecular evolution for anyone doing bioinformatics (since the evolutionary process is what encodes all biological information!), no code examples.
10. Bioinformatics and Molecular Evolution by Higgs and Attwood - good hybrid of basic concepts in molecular evolution and how they connect to bioinformatics, no code examples.

Two nice books to get people interested in biology/bioinformatics are

Games of Life: Explorations in Ecology, Evolution and Behaviour

Fly: An Experimental Life

Still my favorites ;)

Here's a different take to this question. My favorite book is the one that I could write - or the one that Ewan Birney or Lincoln Stein could write (not that I am in their company). In all seriousness, what I am getting at is a kind of interview that is not a digest of a career path but more like this is what I have used and developed in the field of Bioinformatics in response to these challenges (with details) and here is where I required assistance from colleagues who were expert in X or Y. Such a book would certainly sit well on my shelf next to the molecular biology, biochemistry and Perl/R/Java coding books.

(Sorry, this is not an add, even if it sound like...)

My favourite bioinformatics book is a biology book Lewin's Genes X. Of course it's not a bioinformatics book, but is very good for getting a good understanding of the biology. Bio-informatics is an interdisciplinary field and for me, it is the fascination of the related genetics that motivates me to analyse it. I see computer science as a means to better understand genetics. This book can provide the necessary insight into genetics required for good bioinformatics. I cannot read this from cover to cover, it's just too much information, but it provides different levels of detail. Even when reading only the headlines, one could learn something new.

Maybe not so well suited for absolute beginners in genetics, and some biologists say it is superficial sometimes. Might be, but that I cannot judge, I just found the parts I read well understandable. There are of course lots of references (rather many to "Cell").

These are my favorite books which I have been following

• Bioinformatics - A Practical Guide to the analysis of Genes and Proteins-Andreas Baxevanis & B.F.Francis Ouellette..

• Guide to Human Genome Computing-Martin J Bishop

• An Introduction to Bioinformatics-Arthur M. Lesk

• Algorithmic Aspects of Bioinformatics (Natural Computing)- Hans-Joachim Bockenhauer & Dirk Bongartz

• Beginning Perl for Bioinformatics-James Tisdall

• BioPython tutorial and cookbook -Jeff Chang, Brad Chapman, Iddo Friedberg, Thomas Hamelryck, Michiel de Hoon, Peter Cock, Tiago Antao, Eric Talevich

• Algorithms in Bioinformatics: A Practical Introduction- Wing-Kin Sung, National University of Singapore

And Recently I am going through Computational Methods for Mass Spectrometry Proteomics -Ingvar Eidhammer, Kristian Flikka, Lennart Martens, Svein-Ole Mikalsen

Here are soem books I like very much, though NOT in order of preference

1. 'Bioinformatics and Functional Genomics' by Jonathan Pevsner

2. 'Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids' by Durbin, Eddy and Krogh and its accompanying solution manual as suggested by few, by Mark Borodovsky and Svetlana Ekisheva

3. 'Protein Bioinformatics: An Algorithmic Approach to Sequence and Structure Analysis' by Ingvar Eidhammer, Inge Jonassen and William R. Taylor: A fantastic book particularly on protein structural bioinformatics

4. 'Bioinformatics Biocomputing and Perl: An Introduction to Bioinformatics Computing Skills and Practice' by michael moorhouse and paul barry, liked more than the O'Reilly's equivalents.

5. A Practical Introduction to the Simulation of Molecular Systems by Martin Field.

6. The Art of Molecular Dynamics Simulation by DC Rapaport

I think one book that a Person must have in addition to the large repertoire of above mentioned resources (to stay afloat in Bioinformatics) is the trimonthly edition of Wiley "Current Protocols in Bioinformatics".

An excellent list of books so far, some that I hadn't heard of. One book I did not see mentioned is "Inferring Phylogenies" by Felsenstein. While not a general bioinformatics book it is a great resource if one wants to learn about phylogenetic analysis.

Dito Biological Sequence Analysis, Durbin et al. and Alberts for background.

I took my first steps in bioinformatics with Beginning Perl for bioinformatics. Of the other books I've read the one book that I particularly liked is Building bioinformatics solutions.

Almost popular books are here

http://www.bioinformatics.fr/books.php

Best Book For newbie

Bioinformatics - A Practical Guide to the analysis of Genes and Proteins-Andreas Baxevanis & B.F.Francis Ouellette

Bioinformatics Sequence and Genome Analysis, Second Edition - David W. Mount