Computational gene finding in plants.
Automated methods for identifying protein coding regions in genomic DNA have progressed significantly in recent years, but there is still a strong need for more accurate computational solutions to the gene finding problem. Large-scale genome sequencing projects depend greatly on gene finding to generate accurate and complete gene annotation. Improvements in gene finding software are being driven by the development of better computational algorithms, a better understanding of the cell's mechanisms for transcription and translation, and the enormous increases in genomic sequence data. This paper reviews some of the most widely used algorithms for gene finding in plants, including technical descriptions of how they work and recent measurements of their success on the genomes of Arabidopsis thaliana and rice.
Pertea
Mihaela
M
Institute for Genome Research, Rockville, MD 20850, USA. mpertea@tigr.org
Salzberg
Steven L
SL
D000465:Algorithms; D017360:Arabidopsis / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D017343:Genes, Plant / Q000235:genetics*; D010944:Plants / Q000235:genetics*