Chairmen: Dr. A. Ratushny (Institute for Systems Biology, Seattle, USA). Prof. V. P. Golubyatnikov (IM SB RAS, Novosibirsk, Russia), Prof. M.Dehmer (Institute for Bioinformatics and Translational Research, Austria).
The section is devoted to the problems and methods of mathematical analysis of complex biological networks (gene and metabolic networks, associative and semantic networks, protein-protein interactions).
Methods for describing and comparison of complex networks will be discussed, as well as methods for identifying and search for structural patterns, structural motifs and methods of model networks reconstruction. The session includes discussion of comparative analysis of biological networks and networks evolution patterns.
Multiscale modeling methods that combine large-scale globally predictive and small-scale detailed kinetic models represents an effective framework for exploring dynamical biomolecular systems. This combined approach allows the integration of the genome-scale ‘omics’ data, identification of key players in particular cellular functions and iterative investigation of underlying molecular mechanisms using the “experiment-model-hypothesis-experiment” systems biology cycle. While both large scale and detailed kinetic models are available and have shown success in predicting organism behavior, they have not yet been adequately integrated. We are developing computational approaches for multiscale modeling and systematic exploration of topological features and parametric space of dynamical biological systems. Using these approaches we have discovered and modeled novel biomolecular regulatory systems in various organisms including Saccharomyces cerevisiae and Halobacterium salinarum. These studies reveal evolutionary advantages of discovered regulatory systems, principles of operation, and mechanisms for control that are relevant for rational intervention and synthetic biology applications.
The section will include discussion on modeling methods in system computational biology.