DocumentCode
785547
Title
Mining residue contacts in proteins using local structure predictions
Author
Zaki, Mohammed J. ; Jin, Shan ; Bystroff, Chris
Author_Institution
Comput. Sci. Dept., Rensselaer Polytech. Inst., Troy, NY, USA
Volume
33
Issue
5
fYear
2003
Firstpage
789
Lastpage
801
Abstract
In this paper we develop data mining techniques to predict 3D contact potentials among protein residues (or amino acids) based on the hierarchical nucleation-propagation model of protein folding. We apply a hybrid approach, using a hidden Markov model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.
Keywords
biology computing; data mining; hidden Markov models; molecular biophysics; molecular configurations; physiological models; proteins; HMM; association mining; contact potential discovery; folding initiation site extraction; hidden Markov model; hierarchical nucleation-propagation model; local structure predictions; protein folding; protein residue contact mining; Amino acids; Bioinformatics; Data mining; Databases; Genomics; Hidden Markov models; Pattern analysis; Predictive models; Protein engineering; Sequences;
fLanguage
English
Journal_Title
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
1083-4419
Type
jour
DOI
10.1109/TSMCB.2003.816916
Filename
1232716
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