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BMCBI
2006
119views more  BMCBI 2006»
13 years 4 months ago
Hidden Markov Model Variants and their Application
Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
Stephen Winters-Hilt
BMCBI
2007
115views more  BMCBI 2007»
13 years 4 months ago
A novel, fast, HMM-with-Duration implementation - for application with a new, pattern recognition informed, nanopore detector
Background: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) ...
Stephen Winters-Hilt, Carl Baribault
BMCBI
2006
155views more  BMCBI 2006»
13 years 4 months ago
CAVER: a new tool to explore routes from protein clefts, pockets and cavities
Background: The main aim of this study was to develop and implement an algorithm for the rapid, accurate and automated identification of paths leading from buried protein clefts, ...
Martin Petrek, Michal Otyepka, Pavel Banás,...