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BMCBI
2006
119views more  BMCBI 2006»
13 years 5 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
PR
2010
147views more  PR 2010»
13 years 4 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
SSPR
2004
Springer
13 years 11 months ago
Tracking the Evolution of a Tennis Match Using Hidden Markov Models
The creation of a cognitive perception systems capable of inferring higher-level semantic information from low-level feature and event information for a given type of multimedia co...
Ilias Kolonias, William J. Christmas, Josef Kittle...
BMCBI
2006
118views more  BMCBI 2006»
13 years 5 months ago
Automatic generation of gene finders for eukaryotic species
Background: The number of sequenced eukaryotic genomes is rapidly increasing. This means that over time it will be hard to keep supplying customised gene finders for each genome. ...
Kasper Munch, Anders Krogh
ISMB
1997
13 years 7 months ago
Functional Prediction of B. subtilis Genes from Their Regulatory Sequences
In bacterial cells, gene expression is regulated by multiple sigma factors, each of which has its promoter specificity, according to their conditions. Thus, if we can discriminate...
Tetsushi Yada, Yasushi Totoki, Takahiro Ishii, Ken...