New methods for splice site recognition

Sören Sonnenburg, Gunnar Rätsch, Arun Jagota, Klaus Robert Müller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)


Splice sites are locations in DNA which separate protein-coding regions (exons) from noncoding regions (introns). Accurate splice site detectors thus form important components of computational gene finders. We pose splice site recognition as a classification problem with the classifier learnt from a labeled data set consisting of only local information around the potential splice site. Note that finding the correct position of splice sites without using global information is a rather hard task. We analyze the genomes of the nematode Caenorhabditis elegans and of humans using specially designed support vector kernels. One of the kernels is adapted from our previous work on detecting translation initiation sites in vertebrates and another uses an extension to the well-known Fisher-kernel. We find excellent performance on both data sets.

Original languageEnglish
Title of host publicationArtificial Neural Networks, ICANN 2002 - International Conference, Proceedings
EditorsJose R. Dorronsoro, Jose R. Dorronsoro
PublisherSpringer Verlag
Number of pages8
ISBN (Print)9783540440741
Publication statusPublished - 2002
Externally publishedYes
Event2002 International Conference on Artificial Neural Networks, ICANN 2002 - Madrid, Spain
Duration: 2002 Aug 282002 Aug 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2415 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2002 International Conference on Artificial Neural Networks, ICANN 2002

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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