CONTRAST 1.0

:: DESCRIPTION

CONTRAST predicts protein-coding genes from a multiple genomic alignment using a combination of discriminative machine learning techniques. A two-stage approach is used, in which output from local classifiers is combined with a global model of gene structure. CONTRAST is trained using a novel procedure designed to maximize expected coding region boundary detection accuracy.

::DEVELOPER

Chuong Do (chuongdo@cs.stanford.edu)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

• Linux

:: DOWNLOAD

 CONTRAST

:: MORE INFORMATION

Citation

Gross SS, Do CB, Sirota M, Batzoglou S.
CONTRAST: A Discriminative, Phylogeny-free Approach to Multiple Informant De Novo Gene Prediction.
Genome Biology, submitted.