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.
Thank you for your visit. For further details, please use the menu on the left hand side.
News
Recently, we received an ERC-starting-grant for modeling latent causes in molecular networks. Please check our open positions if you are interested.
We welcome our newest group members Nikola Müller and Justin Feigelman.
We are happy to announce the release of Applications of MATLAB in Science and Engineering
The chapter From Discrete to Continuous Gene Regulation Models – A Tutorial Using the Odefy Toolbox has been written by Jan Krumsiek, Dominik M. Wittmann and Fabian J. Theis
We are always looking for interested diploma and PhD students! Email or visit us to get more details!
Selected recent publications
| [1] | I. Laaser, F. Theis, M. H. de Angelis, H. Kolb and J. Adamski. Huge Splicing Frequency in Human Y Chromosomal UTY Gene. OMICS A journal of Integrative Biology, 15(3):141-154, 2011. 10.1089/omi.2010.0107. [ DOI | PubMed | .pdf ] |
| [2] | A. Kowarsch, M. Preusse, C. Marr and F. Theis. miTALOS: analyzing the tissue-specific regulation of signaling pathways by human and mouse microRNAs. RNA, accepted, 2011. 10.1261/rna.2474511. [ DOI | PubMed ] |
| [3] | F. Theis, N. Latif, P. Wong and D. Frishman. Complex principal component and correlation structure of 16 yeast genomic variables. Molecular Biology and Evolution, accepted, 2011. 10.1093/molbev/msr077. [ DOI | PubMed | .pdf ] |
| [4] | J. Krumsiek, K. Suhre, T. Illig, J. Adamski and F. Theis. Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data. BMC Systems Biology, 5(21), 2011. 10.1186/1752-0509-5-21. [ DOI | PubMed | .pdf ] |
| [5] | F. Theis, S. Bohl and U. Klingmüller. Theoretical analysis of time-to-peak responses in biological reaction networks. Bulletin of Mathematical Biology, 73(5):978-1003, 2011. 10.1007/s11538-010-9548-x. [ DOI | PubMed | .pdf ] |
| [6] | M. Hartsperger, F. Blöchl, V. Stümpflen and F. Theis. Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs. BMC Bioinformatics, 11(522), 2010. 10.1186/1471-2105-11-522. [ DOI | PubMed | .pdf ] |
| [7] | W. Konopka, A. Kiryk, M. Novak, M. Herwerth, J. R. Parkitna, M. Wawrzyniak, A. Kowarsch, P. Michaluk, T. Arnsperger, G. Wilczynski, M. Merkenschlager, F. Theis, G. Köhr, L. Kaczmarek and G. Schütz. MicroRNA loss enhances learning and memory in mice. Journal of Neuroscience, 30(44):14835-14842, 2010. 10.1523/JNEUROSCI.3030-10.2010. [ DOI | PubMed | .pdf ] |
| [8] | D. Wittmann, C. Marr and F. Theis. Biologically meaningful update rules increase the critical connectivity of generalized Kauffman networks. Journal of Theoretical Biology, 266:436-448, 2010. 10.1016/j.jtbi.2010.07.007. [ DOI | PubMed | .pdf ] |
| [9] | A. Kowarsch, C. Marr, D. Schmidl, A. Ruepp and F. Theis. Tissue-specific target analysis of disease-associated microRNAs in human signaling pathways. PLoS ONE, 5(6):e11154, 2010. 10.1371/journal.pone.0011154. [ DOI | PubMed | .pdf ] |
| [10] | C. Marr, F. Theis, L. Liebovitch and M. Hütt. Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli. PLoS Computational Biology, 6(7):e1000836, 2010. 10.1371/journal.pcbi.1000836. [ DOI | PubMed | .pdf ] |
