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Introduction to Computational Genomics: A Case Studies Approach ISBN 0521671914
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Standort: Silver Spring, Maryland, USA
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eBay-Artikelnr.:116563792717
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- “Slight shelf wear. Some water damage.”
- ISBN
- 9780521671910
Über dieses Produkt
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
0521671914
ISBN-13
9780521671910
eBay Product ID (ePID)
52036857
Product Key Features
Number of Pages
202 Pages
Publication Name
Introduction to Computational Genomics : a Case Studies Approach
Language
English
Publication Year
2006
Subject
Life Sciences / Genetics & Genomics, Bioinformatics, Life Sciences / Biology
Type
Textbook
Subject Area
Computers, Science
Format
Perfect
Dimensions
Item Height
0.4 in
Item Weight
13.1 Oz
Item Length
9.7 in
Item Width
7.4 in
Additional Product Features
Intended Audience
College Audience
LCCN
2007-273397
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
572.86072
Table Of Content
Prologue (in praise of cells); 1. The first look at a genome (sequence statistics); 2. All the sequence's men (gene finding); 3. All in the family (sequence alignment); 4. The boulevard of broken genes (hidden Markov models); 5. Are Neanderthals among us? (variation within and between species); 6. Fighting HIV (natural selection at the molecular level); 7. SARS: a post-genomic epidemic (phylogenetic analysis); 8. Welcome to the hotel Chlamydia (whole genome comparisons); 9. The genomics of wine-making (analysis of gene expression); 10. A bed-time story (identification of regulatory sequences); Appendix.
Synopsis
Are we related to Neanderthals? Where did SARS come from? Such questions are answered by statistical and computational analysis of genetic data, and are the vehicle for this entertaining introduction to computational genomics. The case-studies approach with Matlab demos provides an enjoyable way to learn how to analyze genomic data first-hand., Where did SARS come from? Have we inherited genes from Neanderthals? How do plants use their internal clock? The genomic revolution in biology enables us to answer such questions. But the revolution would have been impossible without the support of powerful computational and statistical methods that enable us to exploit genomic data. Many universities are introducing courses to train the next generation of bioinformaticians: biologists fluent in mathematics and computer science, and data analysts familiar with biology. This readable and entertaining book, based on successful taught courses, provides a roadmap to navigate entry to this field. It guides the reader through key achievements of bioinformatics, using a hands-on approach. Statistical sequence analysis, sequence alignment, hidden Markov models, gene and motif finding and more, are introduced in a rigorous yet accessible way. A companion website provides the reader with Matlab-related software tools for reproducing the steps demonstrated in the book., Self-contained and entertaining introduction to computational genomics, using a case-studies approach with Matlab demos.
LC Classification Number
QH438.4
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