Bioinformatics for Biologists

A team of renowned bioinformaticians take innovative approaches to lead biology students from first principles towards computational thinking.

Pavel Pevzner (Edited by), Ron Shamir (Edited by)

9781107011465, Cambridge University Press

Hardback, published 15 September 2011

394 pages, 37 b/w illus. 105 colour illus. 4 tables
25.2 x 19.5 x 2.2 cm, 0.99 kg

'This volume represents an excellent [effort] towards creating an interesting and useful introductory bioinformatics text. In its current form it may benefit computational scientists more than biologists, but has the potential to evolve into an invaluable resource for all bioinformaticists, independent of their primary field of study.' Dimitris Papamichail, SIGACT News

The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors - each a leading scientist - engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers.

Preface
Acknowledgements
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
Index.

Subject Areas: Computer science [UY], Molecular biology [PSD], Genetics [non-medical PSAK]