Splice form prediction using Machine Learning

author: Gunnar R├Ątsch, Max Planck Institute
published: Feb. 25, 2007,   recorded: August 2006,   views: 4795

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Accurate ab initio gene finding is still a major challenge in computational biology. We employ state-of-the-art machine learning techniques based on Hidden Semi-Markov-SVMs to assay and improve the accuracy of genome annotations. We applied our system, called mSplicer, on the Caenorhabditis elegans genome and were able to drastically improve its annotation.

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