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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.
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 Puigb# 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 Natasa Przulj
16. Regulatory network inference Russell Schwartz
Pavel Pevzner is Ronald R. Taylor Professor of Computer Science and Director of the Bioinformatics and Systems Biology Program at the University of California, San Diego. He was named a Howard Hughes Medical Institute Professor in 2006.
Ron Shamir is the Raymond and Beverly Sackler Professor of Bioinformatics and Head of the Edmond J. Safra Bioinformatics Program at Tel Aviv University. He founded the joint Life Sciences/Computer Science undergraduate degree program in Bioinformatics at Tel Aviv University.
"This volume contains a remarkable collection of individually-authored chapters cutting a wide swathe across the field as it is currently constituted. What is noteworthy, aside from the wide angle of the snapshot of today's bioinformatics, something the editors promise to update in future editions, is the innovative and effective pedagogical emphasis apparent throughout [...] The editors set out to provide a resource for teaching bioinformatics to life science undergraduates, and this is reflected in the language, organization and mathematical restraint of the different chapters [...] It is highly suitable as a text or reference for bioinformatics courses at the graduate level, for biologists, medical students and computer scientists. Biological naïveté in thinking and writing plagues bioinformatics, and Pevzner and Shamir's Bioinformatics for Biologists offers a wonderful therapy for that condition as well as an effective palliative for life science students' math phobias."
– Professor David Sankoff, University of Ottawa
"A serious and valuable effort to bring essential and much-needed training in the computational sciences to students of modern biology."-
– Michael Waterman, University of Southern California
"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