Gunnar Raetsch's profile

What I do

I am a group leader at the Friedrich Miescher Laboratory of the Max Planck Society in Tübingen working on Machine learning and its applications in computational biology.

Affiliations

Current

Location

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Interests

I am are interested in modern machine learning techniques suitable for the analysis of problems arising in genome biology. In my group we develop new learning techniques that (a) are capable of dealing with large amounts of genomic data, (b) allow for very accurate predictions on the biological phenomenon at hand and© are able to comprehensibly provide reasons for their prognoses, and thereby assist in gaining new biological insights.

Projects

Together with my colleagues, I am considering novel methods for ab initio gene finding, the development of novel alignment algorithms, the prediction of alternative splicing, and the analysis of tiling array data.

Publications

  • Detecting Polymorphic Regions in the Arabidopsis thaliana Genome with Resequencing Microarrays. Genome research (2008) (Epub 06 Mar 2008) PubMed ID:(18323538)

  • Clark R, Schweikert G, Toomajian C, Ossowski S, Zeller G, Shinn P, Warthmann N, Hu T, Fu G, Hinds D, Chen H, Frazer K, Huson D, Schölkopf B, Nordborg M, Rätsch G, Ecker J, Weigel D. Common sequence polymorphisms shaping genetic diversity in Arabidopsis thaliana. Science (New York, N.Y.) 317 (5836) , 338-42 PubMed ID:(17641193)

  • Müller K, Rätsch G, Sonnenburg S, Mika S, Grimm M, Heinrich N. Classifying 'drug-likeness' with kernel-based learning methods. Journal of chemical information and modeling 45 (2) , 249-53 PubMed ID:(15807485)

  • Rätsch G, Sonnenburg S, Schäfer C. Learning interpretable SVMs for biological sequence classification. BMC bioinformatics 7 Suppl 1 , S9 (Epub 20 Mar 2006) PubMed ID:(16723012)

  • Rätsch G, Sonnenburg S, Schölkopf B. RASE: recognition of alternatively spliced exons in C.elegans. Bioinformatics (Oxford, England) 21 Suppl 1 , i369-77 PubMed ID:(15961480)

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