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Bhak, Jong
KOrean GenomIcs Center(KOGIC)
Research Interests
  • Geromics, genomics, bioinformatics, protein Engineering, OMICS

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FOLD RECOGNITION AND AB-INITIO STRUCTURE PREDICTIONS USING HIDDEN MARKOV-MODELS AND BETA-STRAND PAIR POTENTIALS

Cited 49 times inthomson ciCited 54 times inthomson ci
Title
FOLD RECOGNITION AND AB-INITIO STRUCTURE PREDICTIONS USING HIDDEN MARKOV-MODELS AND BETA-STRAND PAIR POTENTIALS
Other Titles
Update on protein structure predictuibL results of the IRBM 1995 workshop.
Author
HUBBARD, Tim J.Bhak, Jong Hwa
Keywords
PROTEIN STRUCTURE PREDICTION; BETA-STRAND; POTENTIAL OF MEAN FORCE; HIDDEN MARKOV MODEL; MULTIPLE SEQUENCE ALIGNMENT
Issue Date
1995-11
Publisher
WILEY-LISS, DIV JOHN WILEY & SONS INC 605 THIRD AVE, NEW YORK, NY 10158-0012
Citation
Proteins: Structure, Function and Genetics, v.23, no.3, pp.398 - 402
Abstract
Protein structure predictions were submitted for 9 of the target sequences in the competition that ran during 1994. Targets sequences were selected that had no known homology with any sequence of known structure and were members of a reasonably sized family of related but divergent sequences. The objective was either to recognize a compatible fold for the target sequence in the database of known structures or to predict ab initio its rough 3D topology. The main tools used were Hidden Markov models (HMM) for fold recognition, a beta-strand pair potential to predict beta-sheet topology, and the PHD server for secondary structure prediction, Compatible folds were correctly identified in a number of cases and the beta-strand pair potential was shown to be a useful tool for ab initio topology prediction. (C) 1995 Wiley-Liss, Inc
URI
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DOI
10.1002/prot.340230313
ISSN
1097-0134
Appears in Collections:
BME_Journal Papers
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