With DNA sequencing costs falling faster than Moore’s law, the challenge is less to discover what is in the genome but how the biological molecules interact to produce biological function. Molecular interactions are often multivalent to produce complex networks. Biochemical networks operate in time to determine cellular responses to environmental changes and in space within and across boundaries and organelles, and they are subject to the physical laws that apply to all molecules, including the fundamental stochasticity of molecular interactions and chemical reactions. Given data quantities and the potential for complexity that exceed even well-honed, intuitive reasoning, a hallmark of the systems biology approach is to combine experiment and modeling to formulate and test hypotheses. The sessions below were designed to highlight approaches that derive and reveal behaviors of complex networks on molecular, time and distance scales.

Network assembly 

The first session will address novel approaches that allow for assembly of large network models containing many components. Trey Ideker (University of California, San Diego) will describe strategies to combine high-throughput genetic and physical interaction data sets as well as recent work revealing how some aspects of networks change in response to DNA damage and how others do not.