Coordinator:

Laszlo Barabasi (Dept. of Physics, University of Notre Dame)

Participants:

G. Forgacs (Dept. of Physics, University of Missouri, Columbia), J. A. Glazier (Dept. of Physics, University of Notre Dame), G. Hentschel (Dept. of Physics, Emory University), P. Kulesa (Beckmann Institute, California Institute of Technology), D. Chen (Dept. of Computer Science and Engineering, University of Notre Dame), J. Izaguirre (Dept. of Computer Science and Engineering, University of Notre Dame), M. Alber (Dept. of Applied and Computational Mathematics and Statistics, University of Notre Dame) and B. Hu (Dept. of Applied and Computational Mathematics and Statistics, University of Notre Dame), Z. Oltvai (Dept. of Pathology, Northwestern University School of Medicine).

Complex biological functions in living organisms rarely depend on single components. Complex networks govern most functional properties, creating webs of diverse interactions. Networks emerge at different organizational levels, ranging from metabolic and regulatory networks within the cell to intercellular networks. Only recently have we had data on components' interactions, complete, detailed, and reliable enough to allow systematic characterization of functional networks. Network topology reveals general organizing principles, which shed light on network function. Our aim is to combine the expertise of several investigators to create a unified research program to explain the architecture of biological networks. We will first focus on metabolic and regulatory networks, developing tools to characterize their topology, function, and dynamics, and to identify functional modules. We will analyze existing databases on network topology (metabolic and protein interactions) and dynamics (microarray data) and correlate topology and dynamics to determine function. Later, we will apply these techniques to analyze large protein-interaction databases to reveal the chemical architecture of the signaling and cytoskeleton sub-networks, and their interrelations. In addition, the network analysis tools we develop will apply to other networks as well, supporting the other Center Projects.