Open AccessImproving gene recognition accuracy by combiningpredictions from two gene-finding programs
Author(s) -
Sanja Rogić,
B. F. Francis Ouellette,
Alan K. Mackworth
Publication year - 2002
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/18.8.1034
Subject(s) - exon , correctness , computer science , gene prediction , gene , consistency (knowledge bases) , computational biology , genetics , data mining , artificial intelligence , biology , algorithm , genome
Despite constant improvements in prediction accuracy, gene-finding programs are still unable to provide automatic gene discovery with desired correctness. The current programs can identify up to 75% of exons correctly and less than 50% of predicted gene structures correspond to actual genes. New approaches to computational gene-finding are clearly needed.
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