Welcome!
Welcome to the research group 'Computational Modeling in Biology' at the Institute of Bioinformatics and Systems Biology at the Helmholtz Zentrum München - German Research Center for Environmental Health. We are interested in applying methods from biostatistics and statistical machine learning to the analysis of biological problems, ranging from regulatory networks to neural recordings.
Currently, we put most focus on the analysis of microRNA-influenced gene regulation. For this we build qualitative interaction models, if possible transform them into quantitative models and try to fit them to realistic data. Key applications are stem cell differentiation and neural development.
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News
We are happy to announce the release of
Biomedical Signal Analysis
Contemporary Methods and Applications
Fabian J. Theis and Anke Meyer-Bäse
We are happy to welcome our newest members Sabine Hug and Andrea Rinck working on bayesian inference and experimental methods to fuctionally characterize microRNA target interactions in a close collaboration with the Institute of Pharmacology and Toxicology (TUM, Medicine), respectively.
We are always looking for interested diploma and PhD students! Email or visit us to get more details!
Selected recent publications
| [1] | A. Ruepp, A. Kowarsch, D. Schmidl, F. Buggenthin, B. Brauner, I. Dunger, G. Fobo, G. Frishman, C. Montrone and F. Theis. PhenomiR: a knowledgebase for microRNA expression in diseases and biological processes. Genome Biology, 11(1):R6, 2010. 10.1186/gb-2010-11-1-r6. [ DOI ] |
| [2] | K. Webb, W. Norton, D. Trümbach, A. Meijer, J. Ninkovic, S. Topp, D. Heck, C. Marr, W. Wurst, F. Theis, H. Spaink and L. Bally-Cuif. Zebrafish reward mutants reveal novel transcripts mediating the behavioral effects of amphetamine. Genome Biology, 10(7):R81, 2009. 10.1186/gb-2009-10-7-r81. [ DOI | .pdf ] |
| [3] | D. Wittmann, J. Krumsiek, J. Saez-Rodriguez, D. Lauffenburger, S. Klamt and F. Theis. Transforming Boolean Models to Continuous Models: Methodology and Application to T-Cell Receptor Signaling. BMC Systems Biology, 3(98), 2009. 10.1186/1752-0509-3-98. [ DOI | .pdf ] |
| [4] | P. Gruber, A. Meyer-Bäse, S. Foo and F. Theis. ICA, kernel methods and nonnegativity: New paradigms for dynamical component analysis of fMRI data. Engineering Applications of Artificial Intelligence, 22(4-5):497-504, 2009. 10.1016/j.engappai.2008.11.010. [ DOI | .pdf ] |
| [5] | S. Klamt, U. Haus and F. Theis. Hypergraphs and cellular networks. PLoS Computational Biology, 5(5), 2009. 10.1371/journal.pcbi.1000385. [ DOI | .pdf ] |
| [6] | R. Neher, M. Mitkovski, F. Kirchhoff, E. Neher, F. Theis and A. Zeug. Blind source separation techniques for the decomposition of multiply labeled fluorescence images. Biophysical Journal, 96(9):3791-3800, 2009. 10.1016/j.bpj.2008.10.068. [ DOI | .pdf ] |
| [7] | D. Wittmann, F. Blöchl, N. Prakash, D. Trümbach, W. Wurst and F. Theis. Spatial analysis of expression patterns predicts genetic interactions at the mid-hindbrain boundary. PLoS Computational Biology, 5(11):e1000569, 2009. 10.1371/journal.pcbi.1000569. [ DOI | .pdf ] |
| [8] | D. Wittmann, D. Schmidl, F. Blöchl and F. Theis. Reconstruction of graphs based on random walks. Journal of Theoretical Computer Science, 410:3826-3838, 2009. 10.1016/j.tcs.2009.05.026. [ DOI | .pdf ] |
| [9] | D. Brockmann and F. Theis. Money Circulation, Trackable Items, and the Emergence of Universal Human Mobility Patterns. IEEE Pervasive Computing, 7(4):28-35, 2008. 10.1109/MPRV.2008.77. [ DOI | .pdf ] |