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Introduction to computational genomics : [Book] : a case studies approach / Nello Cristianini and Matthew W. Hahn.

By: Contributor(s): Material type: TextTextPublication details: New York : Cambridge University Press, 2007.Description: xvii, 182 pages : illustrations ; 26 cmISBN:
  • 9780521671910 (paperback)
  • 0521671914 (paperback)
  • 9780521856034 (hbk.)
  • 0521856035 (hbk.)
Subject(s): DDC classification:
  • 572.86072 22
LOC classification:
  • QH438.4.S73 C75 2007
NLM classification:
  • 2007 A-303
  • QU 58.5
Other classification:
  • 572.86072
Online resources: Summary: 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.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books Junaid Zaidi Library, COMSATS University Islamabad 572.86072 CRI-I (Browse shelf(Opens below)) Available 53794
Total holds: 0

Includes bibliographical references (p. [173]-178) and index.

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.

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