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» Protein Family Classification Using Sparse Markov Transducer...
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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
BMCBI
2004
101views more  BMCBI 2004»
13 years 7 months ago
A database for G proteins and their interaction with GPCRs
Background: G protein-coupled receptors (GPCRs) transduce signals from extracellular space into the cell, through their interaction with G proteins, which act as switches forming ...
Antigoni L. Elefsinioti, Pantelis G. Bagos, Ioanni...
AUSAI
2008
Springer
13 years 9 months ago
Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
BMCBI
2010
151views more  BMCBI 2010»
13 years 7 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
BMCBI
2010
123views more  BMCBI 2010»
13 years 2 months ago
Predicting conserved protein motifs with Sub-HMMs
Background: Profile HMMs (hidden Markov models) provide effective methods for modeling the conserved regions of protein families. A limitation of the resulting domain models is th...
Kevin Horan, Christian R. Shelton, Thomas Girke