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98
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ICPR
2006
IEEE
16 years 1 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
123
Voted
JCB
2006
215views more  JCB 2006»
15 years 11 days 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...
99
Voted
BIRD
2007
Springer
107views Bioinformatics» more  BIRD 2007»
15 years 6 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...
115
Voted
BMCBI
2004
208views more  BMCBI 2004»
15 years 8 days 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
77
Voted
PSB
2003
15 years 1 months ago
Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models
Kristian Kersting, Tapani Raiko, Stefan Kramer, Lu...