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» Maximum entropy methods for biological sequence modeling
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BIBE
2007
IEEE
167views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
Assessing the Performance of Macromolecular Sequence Classifiers
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...
Cornelia Caragea, Jivko Sinapov, Vasant Honavar, D...
BMCBI
2010
178views more  BMCBI 2010»
13 years 9 months ago
Selecting high-dimensional mixed graphical models using minimal AIC or BIC forests
Background: Chow and Liu showed that the maximum likelihood tree for multivariate discrete distributions may be found using a maximum weight spanning tree algorithm, for example K...
David Edwards, Gabriel C. G. de Abreu, Rodrigo Lab...
RECOMB
2003
Springer
14 years 9 months ago
Modeling dependencies in protein-DNA binding sites
The availability of whole genome sequences and high-throughput genomic assays opens the door for in silico analysis of transcription regulation. This includes methods for discover...
Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kap...
ACL
2006
13 years 10 months ago
Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches
Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing me...
Yuya Unno, Takashi Ninomiya, Yusuke Miyao, Jun-ich...
COLING
2000
13 years 10 months ago
A Hybrid Japanese Parser with Hand-crafted Grammar and Statistics
This paper describes a hybrid parsing method for Japanese which uses both a hand-crafted grammar and a statistical technique. The key feature of our system is that in order to est...
Hiroshi Kanayama, Kentaro Torisawa, Yutaka Mitsuis...