Literature DB >> 12634048

Support vector machines for prediction of protein domain structural class.

Yu-Dong Cai1, Xiao-Jun Liu, Xue-Biao Xu, Kou-Chen Chou.   

Abstract

The support vector machines (SVMs) method was introduced for predicting the structural class of protein domains. The results obtained through the self-consistency test, jack-knife test, and independent dataset test have indicated that the current method and the elegant component-coupled algorithm developed by Chou and co-workers, if effectively complemented with each other, may become a powerful tool for predicting the structural class of protein domains.

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Year:  2003        PMID: 12634048     DOI: 10.1006/jtbi.2003.3179

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  7 in total

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6.  Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.

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Journal:  BMC Bioinformatics       Date:  2009-12-13       Impact factor: 3.169

7.  SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

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Journal:  BMC Bioinformatics       Date:  2008-05-01       Impact factor: 3.169

  7 in total

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