View source for ORF prediction program

ORF prediction progrmas are bioinformatics tools for prediction open reading frames.<br /><br />There have been numerous computational methods for processing prokaryotic genomic ORFs.&nbsp;<br />Most of them are ab initio prediction methods.&nbsp;<br />They provide the genomic coordinates of candidate ORFs using their own statistical and mathematical algorithms:&nbsp;<br />GeneMark <br />ECOPARSE<br />GeneHacker <br />GeneMark.hmm<br />GLIMMER <br />GeneMarkS <br />EasyGene <br />ZCURVE <br />GeneLook <br /><br />However, the ORFs predicted by such programs usually need further time-consuming manual processes. This is mainly due to low accuracy and insufficient evidence. Moreover, their accuracy usually depends on the quality of training sets and/or &lsquo;seed&rsquo; ORFs that need manual validation for better performance. Even though GeneMarkS and GeneLook have increased the prediction accuracy, and GeneLook and the modified EasyGene&nbsp;have automated those manual steps, they still do not provide comprehensive information on predicted ORFs. Information such as frame-shifts, homology-based gene evidence, and best pair-wise matches against other prokaryotes is invaluable for professional curation and large-scale comparative analysis.&nbsp;<br /><br />To complement such ab initio prediction methods, some ORF prediction programs add homology-based methods: ORPHEUS, Critica, FrameD (17), and YACOP (18). ORPHEUS uses the DPS (DNA-Protein Search) program (19) to compare a given genomic sequence with a non-redundant protein sequence databank. FrameD can utilize a BLASTX (20) output provided by the user and provides predicted frame-shifts and conserved regions with other proteins. Critica uses the BLASTN program (20) to align a given genomic sequence with its related sequences chosen from DNA databases. YACOP combines three gene-predicting programs, Critica, Glimmer, and ZCURVE.&nbsp;<br /><br /><br />