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Genome Biol. 2007;8(12):R269.

CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction.

Author information

1
Computer Science Department, Stanford University, Stanford, CA, USA. ssgross@cs.stanford.edu

Abstract

We describe CONTRAST, a gene predictor which directly incorporates information from multiple alignments rather than employing phylogenetic models. This is accomplished through the use of discriminative machine learning techniques, including a novel training algorithm. We use a two-stage approach, in which a set of binary classifiers designed to recognize coding region boundaries is combined with a global model of gene structure. CONTRAST predicts exact coding region structures for 65% more human genes than the previous state-of-the-art method, misses 46% fewer exons and displays comparable gains in specificity.

PMID:
18096039
PMCID:
PMC2246271
DOI:
10.1186/gb-2007-8-12-r269
[Indexed for MEDLINE]
Free PMC Article
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