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An evaluation of contemporary hidden Markov model genefinders with a predicted exon taxonomy
Keith Knapp1, Yi-Ping Phoebe Chen
1Faculty of Science and Technology, Deakin University, Australia. kdk@deakin.edu.au
Abstract:
We present an independent evaluation of six recent hidden Markov model (HMM) genefinders. Each was tested on the new dataset (FSH298), the results of which showed no dramatic improvement over the genefinders tested five years ago. In addition, we introduce a comprehensive taxonomy of predicted exons and classify each resulting exon accordingly. These results are useful in measuring (with finer granularity) the effects of changes in a genefinder. We present an analysis of these results and identify four patterns of inaccuracy common in all HMM-based results.
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