Splice Form Prediction using Machine Learning

Raetsch, G; Rätsch, G; Sonnenburg, S; Srinivasan, J; Müller, K-R; Sommer, R; Schölkopf, B

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Splice Form Prediction using Machine Learning

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Sommer, R
Department Integrative Evolutionary Biology, Max Planck Institute for Developmental Biology, Max Planck Society;

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https://www.iscb.org/cms_addon/conferences/ismb2006/archive/ismb2006.cbi.cnptia.embrapa.br/posters_list.php
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Citation

Raetsch, G., Rätsch, G., Sonnenburg, S., Srinivasan, J., Müller, K.-R., Sommer, R., et al. (2006). Splice Form Prediction using Machine Learning. Poster presented at 14th International Conference on Intelligent Systems for Molecular Biology (ISMB 2006), Fortaleza, Brazil.

Cite as: https://hdl.handle.net/21.11116/0000-000A-7D3A-A

Abstract

Accurate ab initio gene finding is still a major challenge in computational biology. We employ cutting edge machine learning similar to Hidden-Markov-SVMs to assay and improve the accuracy of genome annotations. We applied our system on the C_elegans genome and were able to drastically improve its annotation.