Symbolic Methods for Biological Networks

• Applicants: Professor Dr. Reinhard Klein, since 4/2020; Professor Dr. Andreas Schuppert; Professor Dr. Werner M. Seiler; Professor Dr. Sebastian Walcher
• Subject Area: Mathematics ; Bioinformatics and Theoretical Biology ; Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics ; Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics ; Theoretical Computer Science
• Term: from 2018 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 391322026

Modeling the dynamics of networks is a key challenge in systems medicine and, more generally, in systems biology. Currently applied numeric methods face obstacles like parameter indeterminacy, instability, and curse of dimensionality. We propose new methods for a symbolic analysis, which overcome those obstacles and even impose an entirely new paradigm replacing thinking about single instances with thinking about orders of magnitude. Corresponding computational algebra problems are NP-hard, but experiments point at their feasibility for biological networks. We have already shown that complexity parameters such as tree-width or number of distinct metastable regimes grow only slowly with size for models available in existing biological databases. We will exploit this observation to solve challenging problems in network analysis including determination of parameter regions for the existence and stability of attractors, model reduction, and hybrid modeling of networks.

• DFG Programme: Research Grants
• International Connection: France
• Co-Investigator: Satya Swarup Samal, Ph.D.
• Cooperation Partner: Privatdozent Dr. Thomas Sturm
• Ehemaliger Antragsteller: Professor Dr. Andreas Weber, until 4/2020 (†)