Using database matches with for HMMGene for automated gene detection in Drosophila.
The application of the gene finder HMMGene to the Adh region of the Drosophila melanogaster is described, and the prediction results are analyzed. HMMGene is based on a probabilistic model called a hidden Markov model, and the probabilistic framework facilitates the inclusion of database matches of varying degrees of certainty. It is shown that database matches clearly improve the performance of the gene finder. For instance, the sensitivity for coding exons predicted with both ends correct grows from 62% to 70% on a high-quality test set, when matches to proteins, cDNAs, repeats, and transposons are included. The specificity drops more than the sensitivity increases when ESTs are used. This is due to the high noise level in EST matches, and it is discussed in more detail why this is and how it might be improved.
Krogh
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Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark. krogh@cbs.dtu.dk
D000426:Alcohol Dehydrogenase / Q000235:genetics; D000818:Animals; D019295:Computational Biology / Q000706:statistics & numerical data; D016208:Databases, Factual; D004331:Drosophila melanogaster / Q000201:enzymology / Q000235:genetics*; D017344:Genes, Insect / Q000235:genetics*; D008390:Markov Chains; D009716:Numerical Analysis, Computer-Assisted; D012680:Sensitivity and Specificity; D012689:Sequence Homology, Nucleic Acid; D012984:Software
D000426:Alcohol Dehydrogenase