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00000cam a2200000 7i4500 |
| 001 |
0000078019 |
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20130109093000.0 |
| 008 |
110527s2011 enka eng |
| 020 |
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|a 1107011469 (hardback : alk. paper)
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| 020 |
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|a 1107648874 (paperback : alk. paper)
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| 020 |
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|a 9781107011465 (hardback : alk. paper)
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| 020 |
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|a 9781107648876 (paperback : alk. paper)
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| 050 |
0 |
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|a QH324.2
|b .B56 2011
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| 090 |
0 |
0 |
|a QH324.2
|b .B56 2011
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| 245 |
0 |
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|a Bioinformatics for biologists
|c edited by Pavel Pevzner and Ron Shamir
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| 260 |
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|a Cambridge :
|b Cambridge University Press ,
|c c2011
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| 300 |
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|a xxix, 362 p. :
|b ill. (some col.) ;
|c 26 cm.
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| 504 |
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|a Includes bibliographical references and index
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| 505 |
0 |
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|a 1. Identifying the genetic basis of disease -- 2. Pattern identification in a haplotype block -- 3. Genome reconstruction: a puzzle with a billion pieces -- 4. Dynamic programming: one algorithmic key for many biological locks -- 5. Measuring evidence: who's your daddy? -- 6. How do replication and transcription change genomes? -- 7. Modeling regulatory motifs -- 8. How does influenza virus jump from animals to humans? -- 9. Genome rearrangements -- 10. Comparison of phylogenetic trees and search for a central trend in the "Forest of Life" -- 11. Reconstructing the history of large-scale genomic changes: biological questions and computational challenges -- 12. Figs, wasps, gophers, and lice: a computational exploration of coevolution -- 13. Big cat phylogenies, consensus trees, and computational thinking -- 14. Phylogenetic estimation: optimization problems, heuristics, and performance analysis 15. Biological networks uncover evolution, disease, and gene functions -- 16. Regulatory network inference
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| 520 |
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|a "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"
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| 650 |
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0 |
|a Bioinformatics
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| 700 |
1 |
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|a Pevzner, Pavel ,
|e author
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| 700 |
1 |
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|a Shamir, Ron ,
|e author
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| 999 |
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|a 1000149619
|b Book
|c OPEN SHELF (30 DAYS)
|e Tembila Campus
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| 999 |
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|a 1000149620
|b Book
|c OPEN SHELF (30 DAYS)
|e Tembila Campus
|