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IJCAI
2007
14 years 11 months ago
Incremental Construction of Structured Hidden Markov Models
This paper presents an algorithm for inferring a Structured Hidden Markov Model (S-HMM) from a set of sequences. The S-HMMs are a sub-class of the Hierarchical Hidden Markov Model...
Ugo Galassi, Attilio Giordana, Lorenza Saitta
BMCBI
2005
158views more  BMCBI 2005»
14 years 9 months ago
Automated generation of heuristics for biological sequence comparison
Background: Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. ...
Guy St. C. Slater, Ewan Birney
BMCBI
2010
99views more  BMCBI 2010»
14 years 10 months ago
Prediction of novel precursor miRNAs using a context-sensitive hidden Markov model (CSHMM)
Background: It has been apparent in the last few years that small non coding RNAs (ncRNA) play a very significant role in biological regulation. Among these microRNAs (miRNAs), 22...
Sumeet Agarwal, Candida Vaz, Alok Bhattacharya, As...
COMAD
2008
14 years 11 months ago
REBMEC: Repeat Based Maximum Entropy Classifier for Biological Sequences
An important problem in biological data analysis is to predict the family of a newly discovered sequence like a protein or DNA sequence, using the collection of available sequence...
Pratibha Rani, Vikram Pudi
BMCBI
2004
113views more  BMCBI 2004»
14 years 9 months ago
Oligo kernels for datamining on biological sequences: a case study on prokaryotic translation initiation sites
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...