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BMCBI
2006
121views more  BMCBI 2006»
13 years 4 months ago
Splice site identification using probabilistic parameters and SVM classification
Background: Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and ...
A. K. M. A. Baten, Bill C. H. Chang, Saman K. Halg...
BMCBI
2008
143views more  BMCBI 2008»
13 years 4 months ago
Automatic detection of exonic splicing enhancers (ESEs) using SVMs
Background: Exonic splicing enhancers (ESEs) activate nearby splice sites and promote the inclusion (vs. exclusion) of exons in which they reside, while being a binding site for S...
Britta Mersch, Alexander Gepperth, Sándor S...
BMCBI
2008
93views more  BMCBI 2008»
13 years 4 months ago
Hybrid MM/SVM structural sensors for stochastic sequential data
In this paper we present preliminary results stemming from a novel application of Markov Models and Support Vector Machines to splice site classification of Intron-Exon and Exon-I...
Brian Roux, Stephen Winters-Hilt
ICML
2005
IEEE
14 years 5 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...
RECOMB
2005
Springer
14 years 4 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...