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BMCBI
2005
108views more  BMCBI 2005»
13 years 6 months ago
A linear memory algorithm for Baum-Welch training
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
István Miklós, Irmtraud M. Meyer
WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
14 years 3 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
BMCBI
2004
208views more  BMCBI 2004»
13 years 6 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
2005
87views more  BMCBI 2005»
13 years 6 months ago
Efficient decoding algorithms for generalized hidden Markov model gene finders
Background: The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility an...
William H. Majoros, Mihaela Pertea, Arthur L. Delc...
SC
2005
ACM
13 years 11 months ago
ClawHMMER: A Streaming HMMer-Search Implementation
The proliferation of biological sequence data has motivated the need for an extremely fast probabilistic sequence search. One method for performing this search involves evaluating...
Daniel Reiter Horn, Mike Houston, Pat Hanrahan