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» A Probabilistic Background Model for Tracking
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BMCBI
2008
128views more  BMCBI 2008»
13 years 7 months ago
Finding sequence motifs with Bayesian models incorporating positional information: an application to transcription factor bindin
Background: Biologically active sequence motifs often have positional preferences with respect to a genomic landmark. For example, many known transcription factor binding sites (T...
Nak-Kyeong Kim, Kannan Tharakaraman, Leonardo Mari...
BMCBI
2007
142views more  BMCBI 2007»
13 years 7 months ago
Improving model construction of profile HMMs for remote homology detection through structural alignment
Background: Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addre...
Juliana S. Bernardes, Alberto M. R. Dávila,...
BMCBI
2005
87views more  BMCBI 2005»
13 years 7 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...
BMCBI
2004
166views more  BMCBI 2004»
13 years 7 months ago
Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models
Background: Many current gene prediction methods use only one model to represent proteincoding regions in a genome, and so are less likely to predict the location of genes that ha...
Shaun Mahony, James O. McInerney, Terry J. Smith, ...
BMCBI
2007
173views more  BMCBI 2007»
13 years 7 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...