Our chair takes part in the recently founded International Research Training School RECESS (Regulation and Evolution of Cellular Systems), which is a cooperation of the TUM, LMU and Moscow State Universtiy (MSU). The main research goal is to gain new insight into the regulation and evolution of complex cellular systems by uniting approaches from various fields of research (such as bioinformatics, bioengineering, biology and biochemistry). Our research group is going to use Machine Learning approaches on transcriptome and proteome data to infer biological networks for further analysis.
Pesch, R, Böck, M, and Zimmer, R
ConReg: Analysis and Visualization of Conserved Regulatory Networks in Eukaryotes
In: Proceedings of the German Conference on Bioinformatics (GCB) 2012, Open Access Series in Informatics of the Schloss Dagstuhl (accepted).
Böck, M, Schmitt, C, and Kramer, S
A Study of Dynamic Time Warping for the Inference of Gene Regulatory Relationships
In: Proceedings of the Fifth International Workshop on Machine Learning in Systems Biology (MLSB11), ed. by S. Kramer and N. Lawrence, pp. 6-9.
Schmitt, C, Böck, M, and Kramer, S
SOM Biclustering of Gene Expression Data
In: Proceedings of the Fifth International Workshop on Machine Learning in Systems Biology (MLSB11), ed. by S. Kramer and N. Lawrence, pp. 78-81.