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ICPR
2006
IEEE
14 years 6 months ago
Protein Fold Recognition using a Structural Hidden Markov Model
Protein fold recognition has been the focus of computational biologists for many years. In order to map a protein primary structure to its correct 3D fold, we introduce in this pa...
Djamel Bouchaffra, Jun Tan
JCB
2006
215views more  JCB 2006»
13 years 5 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...
BIRD
2007
Springer
107views Bioinformatics» more  BIRD 2007»
13 years 11 months ago
Prediction of Structurally-Determined Coiled-Coil Domains with Hidden Markov Models
The coiled-coil protein domain is a widespread structural motif known to be involved in a wealth of key interactions in cells and organisms. Coiled-coil recognition and prediction ...
Piero Fariselli, Daniele Molinini, Rita Casadio, A...
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