Improving the protein fold recognition accuracy of a reduced state-space hidden Markov model

Computers in Biology and Medicine

Volumn 39, Issue 10, 2009, Pages 907-914

  Lampros, Christos ^a,b   Papaloukas, Costas ^a   Exarchos, Kostas ^a,b   Fotiadis, Dimitrios I ^a,c   Tsalikakis, Dimitrios ^a,d  

^a UNIVERSITY OF IOANNINA   (Greece)

^b UNIVERSITY OF IOANNINA   (Greece)

^c INSTITUTE OF COMPUTER SCIENCE   (Greece)

^d UNIVERSITY OF WESTERN MACEDONIA   (Greece)

Author keywords

Fold recognition; Hidden Markov models; Protein classification; Secondary structure alphabet; Secondary structure prediction

Indexed keywords

EFFICIENT ARCHITECTURE; FOLD RECOGNITION; LOW COMPLEXITY; MODEL ARCHITECTURE; PHARMACEUTICAL INDUSTRY; PROTEIN CLASSIFICATION; PROTEIN DATA BANK; PROTEIN FOLD RECOGNITION; PROTEIN FUNCTIONS; REDUCED-STATE; SECONDARY STRUCTURE ALPHABET; SECONDARY STRUCTURE PREDICTION; SECONDARY STRUCTURES; TEST SETS; TRAINING ALGORITHMS;

ARCHITECTURAL DESIGN; COMPUTATIONAL COMPLEXITY; COMPUTATIONAL GRAMMARS; DRUG PRODUCTS PLANTS; OBJECT RECOGNITION; PROTEIN FOLDING;

HIDDEN MARKOV MODELS;

PROTEIN;

ACCURACY; ALGORITHM; ARTICLE; CONTROLLED STUDY; HIDDEN MARKOV MODEL; MAXIMUM LIKELIHOOD METHOD; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN DATA BANK; PROTEIN DATABASE; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; SCORING SYSTEM; SEQUENCE ANALYSIS;

MARKOV CHAINS; PROTEIN FOLDING; PROTEINS;

EID: 68849088735     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2009.07.007     Document Type: Article

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