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BMCBI
2006
143views more  BMCBI 2006»
13 years 4 months ago
Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction
Background: One of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because ...
Eric D. Scheeff, Philip E. Bourne
BMCBI
2004
208views more  BMCBI 2004»
13 years 4 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein
NAR
2006
119views more  NAR 2006»
13 years 4 months ago
HHsenser: exhaustive transitive profile search using HMM-HMM comparison
HHsenser is the first server to offer exhaustive intermediate profile searches, which it combines with pairwise comparison of hidden Markov models. Starting from a single protein ...
Johannes Söding, Michael Remmert, Andreas Bie...
BMCBI
2006
102views more  BMCBI 2006»
13 years 4 months ago
Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
Background: The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algor...
Zafer Aydin, Yucel Altunbasak, Mark Borodovsky
ISMB
1994
13 years 5 months ago
Stochastic Motif Extraction Using Hidden Markov Model
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