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BMCBI
2011
12 years 11 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...
BMCBI
2007
144views more  BMCBI 2007»
13 years 7 months ago
Application of amino acid occurrence for discriminating different folding types of globular proteins
Background: Predicting the three-dimensional structure of a protein from its amino acid sequence is a long-standing goal in computational/molecular biology. The discrimination of ...
Y.-h. Taguchi, M. Michael Gromiha
JCB
2006
215views more  JCB 2006»
13 years 7 months ago
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation con...
Yan Liu 0002, Jaime G. Carbonell, Peter Weigele, V...
BMCBI
2008
123views more  BMCBI 2008»
13 years 7 months ago
Validation of protein models by a neural network approach
Background: The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure re...
Paolo Mereghetti, Maria Luisa Ganadu, Elena Papale...
JUCS
2010
104views more  JUCS 2010»
13 years 6 months ago
Investigating a Correlation between Subcellular Localization and Fold of Proteins
: When considering the prediction of a structural class for a protein as a classification problem, usually a classifier is based on a feature vector x ∈ Rn , where the features...
Johannes Aßfalg, Jing Gong, Hans-Peter Krieg...