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    » Identifying Structural Motifs in Proteins
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    BMCBI
    2006
    116views more  BMCBI 2006»
    Optimized mixed Markov models for motif identification
    13 years 9 months ago
    Optimized mixed Markov models for motif identification
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    Background: Identifying functional elements, such as transcriptional factor binding sites, is a fundamental step in reconstructing gene regulatory networks and remains a challengi...
    Weichun Huang, David M. Umbach, Uwe Ohler, Leping ...
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    BMCBI
    2006
    178views more  BMCBI 2006»
    MannDB - A microbial database of automated protein sequence analyses and evidence integration for protein characterization
    13 years 9 months ago
    MannDB - A microbial database of automated protein sequence analyses and evidence integration for protein characterization
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    Background: MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the dev...
    Carol L. Ecale Zhou, Marisa Lam, Jason Smith, Adam...
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    PSB
    2003
    128views Applied Computing» more  PSB 2003»
    Automated Construction of Structural Motifs for Predicting Functional Sites on Protein Structures
    13 years 11 months ago
    Automated Construction of Structural Motifs for Predicting Functional Sites on Protein Structures
    Download  psb.stanford.edu
    Mike P. Liang, Douglas L. Brutlag, Russ B. Altman
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    BMCBI
    2008
    66views more  BMCBI 2008»
    FunClust: a web server for the identification of structural motifs in a set of non-homologous protein structures
    13 years 10 months ago
    FunClust: a web server for the identification of structural motifs in a set of non-homologous protein structures
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    Gabriele Ausiello, Pier Federico Gherardini, Paolo...
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    ISMB
    1994
    121views Computational Biology» more  ISMB 1994»
    Stochastic Motif Extraction Using Hidden Markov Model
    13 years 11 months ago
    Stochastic Motif Extraction Using Hidden Markov Model
    Download  www.aaai.org
    In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
    Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
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