computational
modeling in biology

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Funding

 

A list of the projects we are currently involved in:

  • ERC-Starting-Grant LatentCauses

    In biology all models are necessarily too simple. In the ERC proposal ‘Modeling latent causes in molecular networks’ or LatentCauses for short, we want to guide model extensions using signal processing. We expect impact of the proposal not only in the fact that we establish links between signal processing and dynamical systems, but also in the import of methods to systems biology from other areas, as well as the export of novel problems to signal processing and dynamical systems. A long-term biological result may be efficient differentiation protocols for example for cell replacement therapy. So by guiding the modeling process using signal processing methods, we will arrive at more relevant models.

  • LungSys (BMBF Medsys Initiative)
    LungSys is a highly interdisciplinary consortium with members from medicine, biochemistry, cell biology, medical imaging, chemistry, physics, mathematics and industry. Its mission is to identify the role of the EpoR in tumor progression, and design strategies that lead to improved therapeutic outcomes. LungSys employs a Systems Biology approach that is capable of integrating experimental data generated by molecular biology and clinical research by mathematical models and addressing emergent properties arising from dynamic behavior.

  • Hepatosys, virtual liver (BMBF) (update of homepage to 3rd grant iteration in progress)
    We are involved in the analysis of combined mRNA and microRNA profiles. The goal is to predict downstream answers of the developed signaling models in collaboration with the Klingmüller group and various modeling groups.

  • Inkombio is a Priority Program of the German Research Foundation (DFG - Deutsche Forschungsgemeinschaft).
    In this project we will extend a physical model for the binding of microRNAs to the corresponding target and establish an extended set of features influencing binding probabilities. We will be faced with the challenge of (i) too many features and (ii) few known interactions on which to train any prediction algorithm. This problem will be solved by using (i) information-theoretical criteria for feature reduction, (ii) regularization, (iii) application of the Infomax approach to guarantee minimal loss of information after dimension reduction, and (iv) experimental validation of theoretical predictions using a novel test system.
  • The Priority Program Pluripotency and Cellular Reprogramming of the German Research Foundation DFG is in its 2nd funding period and aims at the identification and characterization of genetic and epigenetic networks that control pluripotency and mechanisms governing the reinstatement of pluripotency in a differentiated cell.
    In our project, we propose to use stochastic multi-scale modeling techniques to further our understanding of stem cell maintenance and exit of pluripotency. Our key goals are (a) the integration of diverse information into a single model of pluripotency, (b) the prediction of novel molecular interactions and (c) quantitative predictions on systems perturbations e.g. for reprogramming.
  • QBM - Quantitative Biosciences Munich
    This newly established School is designed to prepare young life scientists for the emerging era of quantitative, systems-oriented bioscience. It provides an innovative, integrated PhD training program that is international in outlook and brings together a range of diverse disciplines, from biochemistry and medicine to bioinformatics, experimental and theoretical (bio-)physics, and applied mathematics. Both student research projects and classroom teaching are highly interdisciplinary, with a thematic focus on the problem of gene regulation in all its facets. The School is a joint initiative by leading scientists from the Ludwig-Maximilians-University (LMU) Munich as well as from the Max-Planck Institute of Biochemistry and the Helmholtz Center Munich.
  • Stromal Aging (BMBF GerontoSys Initiative)
    The general endeavor of Stromal Aging is to develop a systems biology approach to further a fundamental understanding of fibroblast aging and possibly fibroblast rejuvenation.
    The contribtion of CMB is to provide both supervised (classification) and unsupervised (mining) analysis of data generated in the experimental work packages. Moreover a combination of the microarray measurements with bioinformatics tools will identify significantly targeted pathways for inclusion in the modeling. For the latter, we will focus on microRNA regulation.
  • BioSysNet (Bavarian Research Network for Molecular Biosystems)
    The analysis of complex biological regulatory systems is an interdisciplinary undertaking which requires the coordinated cooperation of biochemistry, genetics, bioinformatics, biophysics and medicine. By applying innovative methods, the bavarian research network investigates the regulation of the genome on cellular as well as molecular level.
    The contribution of CMB in this network is to quantify regulatory mechanisms on the transcriptional level based on time-lapse microscopy of differentiating stem cells. The goal is to learn a predictor in order to accurately determine the time-point of cellular fate decision on the single-cell level, thus allowing experimentation at the decision event.

  • MIMOmics
    In MIMOmics we aim to develop statistical methods for the integrated analysis and interpretation of multiple omics platforms. The goal is to develop methodologies for each analysis step required to identify biomarkers from complex datasets with high dimensionality.
    The contribution of CMB in this consortium is to develop statistical methods capable to identify biomarkers on the basis of data-derived biological networks.

  • Further projects we are currently involved in:

 

 

 

Finished projects:

  • algorithms for fMRI data analysis for modelling of cognitive processes in the human brain in the project 'ModKog' funded by the  BMBF (finished 2006)
  • CoReNe (Helmholtz Alliance on Systems Biology)
    CoReNe stands for Control of Regulatory Networks. Regulatory networks are essential to the understanding of central biological processes such as stem cell differentiation, pattern formation, and mitochondrial biogenesis. They are built from different types of components such as signalling receptors, signalling cascades, transcription factors, and microRNAs. The latter class of regulators is known to orchestrate cellular processes by translational inhibition. The challenge addressed in the CoReNe project is the search for principles underlying gene regulation with a focus on microRNAs.

  • SysMBo (BMBF Medsys Initiative)
    In Systems Biology of Metabolic Phenotypes (SysMbo) we aim to combine information from genetic variation with information gained by quantitative MS/MS analysis of metabolic profiles from serum and tissue samples. Our goal is to uncover genotype/environment/phenotype relations with an emphasis on lipid metabolism and to make relevant contributions to the understanding of disease mechanisms.
    The contribution of CMB in this consortium is to develop quantitative metabolic models. For each study (population genetics, nutritional challenging, metabolic mouse models, mitochondriopathies and rare diseases) and each experimental stage, we will develop a quantitative, local pathway model that integrates the relevant experimental perturbation. This model will be used to predict future experimental variations.