Bioi 7711 textbook options
The following books are excellent, although none of them covers everything you need to know. We have lab copies (that need to stay in the lab) and the library owns them (if you want to check them out). I'd suggest owning at least a couple of them for your reference during class. [The links are to Amazon, but don't take that as an endorsement to buy from them over anyone else.]- An Introduction to Bioinformatics Algorithms by Neil C. Jones & Pavel A. Pevzner. This is a good introduction for those who are coming from a computer science algorithms background, and for others, provides a strong theoretical foundation for many of the general computational approaches that have been productive in biology.
- Statistical Methods in Bioinformatics by Warren Ewens & Gregory Grant. An ambitious book, that contains nearly all the statistics that a bioinformatician ought to know (and a bit more). You should be comfortable with most of the ideas in this book, if not all of the details.
- Bioinformatics from Genomes to Drugs edited by Thomas Lengauer, covers many of the structural topics absent from the two previous, more sequence-oriented books. Two volumes & expensive, but good. The library has a copy if you want to read before you buy.
- Molecular Modeling and Simulation by Tamar Schlick is narrower in scope than Languaer, but much more carefully tailored to student's needs of practicality and a unified theoretical perspective.
- Discovering Genomics, Proteomics and Bioinformatics by Campbell and Heyer is the gentlest place to start for someone from biology, coming with a modest quantitative background. And a good place for others to begin to appreciate why biologists care about all these algorithms.
- Computational Cell Biology by Fall, et al has very nice coverage of the issues involved in dynamical "systems biology" models. Assumes a general knowledge of differential equations.
There are many other good books that might be useful to some of you.
- Pevzner's more advanced textbook, Computational Molecular Biology: An Algorithmic Approach is an awesome compendium of specific problems and well-defined algorithms to solve them. Requires confort with algorithmic computer science to make much sense of it, and doesn't provide a lot of background about why these particular problems are important. However, many problems (in sequence analysis in particular) are very elegantly solved here. Also, this is a good place to find inspiration when you need a more efficient or effective way to solve your own problem.
- Introduction to Bioinformatics by Arthur Lesk. A short, but broad text that assumes a lot of biological knowledge. Good problems at the end of each chapter and a nice companion website
- Bioinformatics and Functional Genomics by Jonathan Pevsner. A big, broad book that provides excellent biological motivation (and caveats!) for each problem addressed with computational tools. An "undergraduate" textbook, it is a good place to go for background when you didn't understand something in class.
- Computational Systems Biology by Uri Alon isn't really a textbook, since it's really just Alon's way of looking at the world, but it is a powerful set of ideas about biological networks presented in a surprisingly accessible way.
- Microarrays for an Integrative Genomics by Isaac S. Kohane, Alvin Kho, and Atul J. Butte. A short book, dedicated exclusively to microarray analysis. Covers all aspects, from scanning images to interpreting the results. Other good microarray analysis books include Statistical analysis of gene expression microarray data by Terry Speed (more technical) and Bioinformatics and Computational Biology Solutions Using R and Bioconductor edited by Robert Gentleman (more hands-on).
- Algorithms on strings, trees, and sequences: computer science and computational biology., by Dan Gusfield. Among the very first books in computational biology (1997) that had a big impact in both computer science and in biology. Accessible for both computer scientists and biologists, and still relevant.
The following are not about bioinformatics, but they are useful for fundamentals you may have missed:
- Fundamentals of Biostatistics by Bernard Rosner. One of many good biostatistics texts. If you are having trouble with Ewans and Grant, try this as a backup.
- Computer Science, an Overview by J. Glenn Brookshear. An excellent introductory computer science textbook. Lots of used copies available, but make sure to get the current (9th) edition. Note that computer science is not the same thing as programming, and that this is not a programming textbook.
- Two excellent introductory Molecular Biology textbooks include Molecular Biology of the Cell by Alberts, et al, (A new edition is to be published shortly) and Molecular Cell Biology by Lodish, et al. Previous editions of these textbooks (and many others) are available for free (in an intentionally awkward format to download) on the NCBI textbook site
