报告题目: Computational Methods for Analysing Long-run Dynamics of Large Biological Networks

报告人： Pang Jun (Associate Researcher，Université du Luxembourg)

主持人: 张敏

报告时间： 12月12日 13:30-15:00更改：12月13日周三 9:00—10:30

报告地点： 中北校区理科大楼B1002室

报告摘要:

         Computational modelling plays a prominent role in providing a system-level understanding of processes that take place in a living cell. However, it faces significant challenges when modelling realistic biological systems due to the size of the state-space that needs to be considered. Hence, profound understanding of biological processes asks for the development of new methods that would provide means for formal analysis and reasoning about large systems.

 Our team takes on this challenge and focuses on gene regulatory networks (GRNs) with respect to their long-run behavior. We consider GRNs cast into the framework of Boolean networks (BNs) or probabilistic Boolean networks (PBNs). Both BNs and PBNs are well-established frameworks for modelling biological systems as they facilitate the modelling of large biological systems as a whole. In this talk, I will summarize our research in the past five years, focusing on

- a decomposition method for attractor detection in BNs, which is the first efficient approach that can deal with large asynchronous BNs with hundreds of nodes;

 - a number of parallelisation techniques for steady-state probability computation for analysing PBNs of up to 1000 nodes.

 I will also give some hints on our current research, exploring both network structure and dynamics to derive optimal control strategies for driving large BNs from a source attractor to a target attractor, which can have important applications in the study of systemic diseases (e.g., cancer).