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

@article{Gross2007, 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.}, author = {Gross, Samuel and Do, Chuong and Sirota, Marina and Batzoglou, Serafim}, citeulike-article-id = {2157379}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/gb-2007-8-12-r269}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/18096039}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=18096039}, day = {20}, doi = {10.1186/gb-2007-8-12-r269}, issn = {1465-6906}, journal = {Genome Biology}, keywords = {annotation, genome, hmm}, month = {December}, number = {12}, pages = {R269+}, posted-at = {2008-11-25 11:51:33}, priority = {2}, title = {CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction}, url = {http://dx.doi.org/10.1186/gb-2007-8-12-r269}, volume = {8}, year = {2007} }

TY - JOUR ID - Gross2007 L3 - citeulike-article-id:2157379 N2 - 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. IS - 12 JF - Genome Biology SN - 1465-6906 TI - CONTRAST: a discriminative, phylogeny-free approach to multiple informant de novo gene prediction VL - 8 SP - R269 KW - annotation KW - genome KW - hmm AU - Gross, Samuel AU - Do, Chuong AU - Sirota, Marina AU - Batzoglou, Serafim PY - 2007/12/20/ UR - http://dx.doi.org/10.1186/gb-2007-8-12-r269 ER -