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ICPR
2006
IEEE
14 years 8 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 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...
BIRD
2007
Springer
107views Bioinformatics» more  BIRD 2007»
14 years 1 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 7 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