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JCB
2000
146views more  JCB 2000»
13 years 5 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
BMCBI
2005
149views more  BMCBI 2005»
13 years 6 months ago
The PD-(D/E)XK superfamily revisited: identification of new members among proteins involved in DNA metabolism and functional pre
Background: The PD-(D/E)XK nuclease superfamily, initially identified in type II restriction endonucleases and later in many enzymes involved in DNA recombination and repair, is o...
Jan Kosinski, Marcin Feder, Janusz M. Bujnicki
JCB
2006
215views more  JCB 2006»
13 years 6 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
2007
113views more  BMCBI 2007»
13 years 6 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...
BMCBI
2004
208views more  BMCBI 2004»
13 years 5 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