Modeling splice sites with Bayes networks | Zendy

D. Michael Cai | Zendy; Arthur L. Delcher | Zendy; Ben Kao | Zendy; Simon Kasif | Zendy

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Modeling splice sites with Bayes networks

Author(s) -

D. Michael Cai,

Arthur L. Delcher,

Ben Kao,

Simon Kasif

Publication year - 2000

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/16.2.152

Subject(s) - bayes' theorem , splice , computer science , computational biology , bayesian probability , bayesian network , artificial intelligence , machine learning , data mining , biology , genetics , gene

The main goal in this paper is to develop accurate probabilistic models for important functional regions in DNA sequences (e.g. splice junctions that signal the beginning and end of transcription in human DNA). These methods can subsequently be utilized to improve the performance of gene-finding systems. The models built here attempt to model long-distance dependencies between non-adjacent bases.

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