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Computational methods in molecular biology / editors, Steven L. Salzberg, David B. Searls, Simon Kasif.

Contributor(s): Series: New comprehensive biochemistry ; v. 32.©1998Description: 1 online resource (xxvi, 371 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780080860930
  • 0080860931
  • 0444828753
  • 9780444828750
Subject(s): Genre/Form: Additional physical formats: Print version:: Computational methods in molecular biology.LOC classification:
  • QD415 .N48eb vol. 32
  • QH506
NLM classification:
  • W1
  • QH 506
Online resources:
Contents:
Grand challenges in computational biology / David B. Searls -- A tutorial introduction to computation for biologists / Steven L. Salzberg -- An introduction to biological sequence analysis / Kenneth H. Fasman, Steven L. Salzberg -- An introduction to hidden Markov models for biological sequences / Anders Krogh -- Case-based reasoning driven gene annotation / G. Christian Overton, Juergen Haas -- Classification-based molecular sequence analysis / David J. States, William C. Reisdorf Jr. -- Computational gene prediction using neural networks and similarity search / Ying Xu, Edward C. Uberbacher -- Modeling dependencies in pre-mRNA splicing signals / Christopher B. Burge -- Evolutionary approaches to computational biology / Rebecca J. Parsons -- Decision trees and Markov chains for gene finding / Steven L. Salzberg -- Statistical analysis of protein structures : using environmental features for multiple purposes / Liping Wei, Jeffrey T. Chang, Russ B. Altman -- Analysis and algorithms for protein sequence-structure alignment / Richard H. Lathrop, Robert G. Rogers Jr., Jadwiga Bienkowska, Barbara K.M. Bryant, Ljubomir J. Buturović, Chrysanthe Gaitatzes, Raman Nambudripad, James V. White, Temple F. Smith -- THREADER : protein sequence threading by double dynamic programming / David Jones -- From computer vision to protein structure and association / Haim J. Wolfson, Ruth Nussinov -- Modeling biological data and structure with probabilistic networks / Simon Kasif, Arthur L. Delcher.
Action note:
  • digitized 2010 HathiTrust Digital Library committed to preserve
Summary: Computational biology is a rapidly expanding field, and the number and variety of computational methods used for DNA and protein sequence analysis is growing every day. These algorithms are extremely valuable to biotechnology companies and to researchers.
Item type: eBooks
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Includes bibliographical references and index.

Grand challenges in computational biology / David B. Searls -- A tutorial introduction to computation for biologists / Steven L. Salzberg -- An introduction to biological sequence analysis / Kenneth H. Fasman, Steven L. Salzberg -- An introduction to hidden Markov models for biological sequences / Anders Krogh -- Case-based reasoning driven gene annotation / G. Christian Overton, Juergen Haas -- Classification-based molecular sequence analysis / David J. States, William C. Reisdorf Jr. -- Computational gene prediction using neural networks and similarity search / Ying Xu, Edward C. Uberbacher -- Modeling dependencies in pre-mRNA splicing signals / Christopher B. Burge -- Evolutionary approaches to computational biology / Rebecca J. Parsons -- Decision trees and Markov chains for gene finding / Steven L. Salzberg -- Statistical analysis of protein structures : using environmental features for multiple purposes / Liping Wei, Jeffrey T. Chang, Russ B. Altman -- Analysis and algorithms for protein sequence-structure alignment / Richard H. Lathrop, Robert G. Rogers Jr., Jadwiga Bienkowska, Barbara K.M. Bryant, Ljubomir J. Buturović, Chrysanthe Gaitatzes, Raman Nambudripad, James V. White, Temple F. Smith -- THREADER : protein sequence threading by double dynamic programming / David Jones -- From computer vision to protein structure and association / Haim J. Wolfson, Ruth Nussinov -- Modeling biological data and structure with probabilistic networks / Simon Kasif, Arthur L. Delcher.

Print version record.

Computational biology is a rapidly expanding field, and the number and variety of computational methods used for DNA and protein sequence analysis is growing every day. These algorithms are extremely valuable to biotechnology companies and to researchers.

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