Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
, 8 (12), 233

Gene Prediction: Compare and CONTRAST

Affiliations
Review

Gene Prediction: Compare and CONTRAST

Paul Flicek. Genome Biol.

Abstract

CONTRAST, a new gene-prediction algorithm that uses sophisticated machine-learning techniques, has pushed de novo prediction accuracy to new heights, and has significantly closed the gap between de novo and evidence-based methods for human genome annotation.

Figures

Figure 1
Figure 1
Increase in the accuracy of de novo gene prediction over time. The gene sensitivity and specificity and the exon sensitivity and specificity on the EGASP test set [5] are shown for several programs by year of initial publication. Included are GENSCAN (1997), TWINSCAN (2001), N-SCAN (2005) and CONTRAST (2007). Note the significant decrease in false positive predictions (as measured by the rise in TWINSCAN's exon specificity) with the inital use of evolutionarily related genome sequences. By comparison, the accuracy of the Ensembl evidence-based gene predictions used in the EGASP experiment at the gene level were 71.6% sensitivity and 67.3% specificity and 77.5% sensitivity and 82.7% specificity at the exon level.

Similar articles

See all similar articles

Cited by 6 articles

See all "Cited by" articles

References

    1. Gross SS, Do CB, Sirota M, Batzoglou S. CONTRAST: A discriminative, phylogeny-free approach to multiple informant de novo gene prediction. Genome Biol. 2007;8(12):r269. - PMC - PubMed
    1. Brent MR. Genome annotation past, present, and future: how to define an ORF at each locus. Genome Res. 2005;15:1777–1786. doi: 10.1101/gr.3866105. - DOI - PubMed
    1. Burge C, Karlin S. Prediction of complete gene structures in human genomic DNA. J Mol Biol. 1997;268:78–94. doi: 10.1006/jmbi.1997.0951. - DOI - PubMed
    1. Flicek P, Keibler E, Hu P, Korf I, Brent MR. Leveraging the mouse genome for gene prediction in human: from whole-genome shotgun reads to a global synteny map. Genome Res. 2003;13:46–54. doi: 10.1101/gr.830003. - DOI - PMC - PubMed
    1. Guigó R, Flicek P, Abril JF, Reymond A, Lagarde J, Denoeud F, Antonarakis S, Ashburner M, Bajic VB, Birney E, et al. EGASP: the human ENCODE Genome Annotation Assessment Project. Genome Biol. 2006;7(Suppl 1):S2. doi: 10.1186/gb-2006-7-s1-s2. - DOI - PMC - PubMed

LinkOut - more resources

Feedback