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BMCBI
2011
12 years 7 months ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
ARTMED
2004
133views more  ARTMED 2004»
13 years 3 months ago
Bayesian network multi-classifiers for protein secondary structure prediction
Successful secondary structure predictions provide a starting point for direct tertiary structure modelling, and also can significantly improve sequence analysis and sequence-stru...
Víctor Robles, Pedro Larrañaga, Jos&...
IPPS
2007
IEEE
13 years 10 months ago
Protein Secondary Structure Prediction using Bayesian Inference method on Decision fusion algorithms
Prediction of protein secondary structure (alpha-helix, beta-sheet, coil) from primary sequence of amino acids is a very challenging task, and the problem has been approached from...
Somasheker Akkaladevi, Ajay K. Katangur
BMCBI
2008
137views more  BMCBI 2008»
13 years 3 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
JCB
2000
146views more  JCB 2000»
13 years 3 months ago
Bayesian Segmentation of Protein Secondary Structure
We present a novel method for predicting the secondary structure of a protein from its amino acid sequence. Most existing methods predict each position in turn based on a local wi...
Scott C. Schmidler, Jun S. Liu, Douglas L. Brutlag