The title of this book would be more descriptive of the contents if it included the word “Genetic” before the current title. Bioinformatics is a very broad field, including all aspects of using information science and computing to store, process and evaluate biological data. In this case the focus is on certain areas of genetics.
The book is a collection of largely distinct chapters written by several authors. All deal with DNA and genes, and several mathematical principles are used in the explanations. The first section describes how the human genome was sequenced by splitting it into a large number of snippets several times and then using algorithms that reconstruct the connections by determining the optimal structure of many segments that have identical overlaps. It was a complex process, with an enormous number of possible combinations. Finding the optimal or best fit was a computational challenge.
Other sections deal with how genes are selectively expressed and repressed, using DNA to establish paternity, developing evolutionary model trees, how viruses manage to jump across species, a computational model for coevolution, the evolutionary tree for big cats, and biological networks. While several areas of mathematics are used, the two most extensively used are graph theory and conditional probability. Graph theory, including random graphs, is used extensively to model the degree of sequential relatedness of species based on their shared and differing genomes.
If your interest is in the general area of bioinformatics, then this book will most likely not be one that you will find worthy of deep study. However, if you are interested in the specialized use of bioinformatics in genetic study, then it should be high on your list of “things to do.”
Charles Ashbacher splits his time between consulting with industry in projects involving math and computers, teaching college classes and co-editing The Journal of Recreational Mathematics. In his spare time, he reads about these things and helps his daughter in her lawn care business.
Introduction Pavel Pevzner and Ron Shamir
Part I. Genomes: 1. Identifying the genetic basis of disease Vineet Bafna
2. Pattern identification in a haplotype block Kun-Mao Chao
3. Genome reconstruction: a puzzle with a billion pieces Phillip Compeau and Pavel Pevzner
4. Dynamic programming: one algorithmic key for many biological locks Mikhail Gelfand
5. Measuring evidence: who's your daddy? Christopher Lee
Part II. Gene Transcription and Regulation: 6. How do replication and transcription change genomes? Andrei Grigoriev
7. Modeling regulatory motifs Sridhar Hannenhalli
8. How does influenza virus jump from animals to humans? Haixu Tang
Part III. Evolution: 9. Genome rearrangements Steffen Heber and Brian Howard
10. The crisis of the tree of life concept and the search for order in the phylogenetic forest Eugene Koonin, Pere Puigbò and Yuri Wolf
11. Reconstructing the history of large-scale genomic changes: biological questions and computational challenges Jian Ma
Part IV. Phylogeny: 12. Figs, wasps, gophers, and lice: a computational exploration of coevolution Ran Libeskind-Hadas
13. Big cat phylogenies, consensus trees, and computational thinking Seung-Jil Sun and Tiffani Williams
14. Algorithm design for large-scale phylogeny Tandy Warnow
Part V. Regulatory Networks: 15. Biological networks uncover evolution, disease, and gene functions Nataša Pržulj
16. Regulatory network inference Russell Schwartz