title: Computational gene prediction using multiple sources of evidence.
abstract: This article describes a computational method to construct gene models by using evidence generated from a diverse set of sources, including those typical of a genome annotation pipeline. The program, called Combiner, takes as input a genomic sequence and the locations of gene predictions from ab initio gene finders, protein sequence alignments, expressed sequence tag and cDNA alignments, splice site predictions, and other evidence. Three different algorithms for combining evidence in the Combiner were implemented and tested on 1783 confirmed genes in Arabidopsis thaliana. Our results show that combining gene prediction evidence consistently outperforms even the best individual gene finder and, in some cases, can produce dramatic improvements in sensitivity and specificity.
authors.affiliation: The Institute for Genomic Research, Rockville, Maryland 20850, USA. jallen@tigr.org
authors.forename: Jonathan E
authors.initials: JE
authors.lastname: Allen
authors.forename: Mihaela
authors.initials: M
authors.lastname: Pertea
authors.forename: Steven L
authors.initials: SL
authors.lastname: Salzberg
mesh_terms: D017360:Arabidopsis / Q000235:genetics; D001482:Base Composition / Q000235:genetics; D001937:Brassica / Q000235:genetics; D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D018076:DNA, Complementary / Q000235:genetics; D018744:DNA, Plant / Q000235:genetics; D017343:Genes, Plant / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D011237:Predictive Value of Tests; D012984:Software / Q000706:statistics & numerical data
chemical_list: D018076:DNA, Complementary; D018744:DNA, Plant