Computer Science Department
Carnegie Mellon University
Graphical models for understanding dynamic systems in the cell
Tuesday, May 2, 2006
Auditorium, Genetics/Biotechnology Center
425 Henry Mall
When studying biological systems such as the cell cycle and stress response one encounters a number of complexity levels. These include the identification of genes that participate in the system, the sub-processes to which they belong and reconstruction of the dynamics of the biological system. Even when focusing on systems that operate in a single cell higher
organizational levels, from tissues to organism, cannot be ignored. In this talk I will present computational methods that rely on graphical models to integrate various types of data from different complexity levels, for understanding and modeling biological systems. These methods allow us to identify a core set of cell cycle genes that are highly conserved in sequence and function and to model the dynamics of yeast response to stress.