DIMACS Workshop on Biomolecular Networks: Topological Properties and Evolution

The functioning of a biological system largely depends on the mutual interactions among its constituent components such as proteins. It is a common practice to represent such a system by a network, within which objects are represented as nodes and relations are represented as edges linking related pairs of nodes. A biological network is broadly defined as any network (graph) where the nodes are identified with some biologically relevant entities and edges define a relation over these entities. For example, in a protein-protein interaction
(PPI) network nodes correspond to proteins and edges to interactions between them; in a metabolic network nodes usually correspond to metabolites and edges to reactions; yet another biological network may be used to describe co-occurrence of protein domains within proteins.
The structure of these biological networks resemble that of many other natural networks such as the world wide web (WWW) graph, where each vertex is a web page, and each edge is a hyperlink from one web page to another. The PPI and the WWW networks both exhibit a power law degree distribution and a small diameter. This is very different from networks generated by standard random graph models which are static and do not have power law degree distribution. Furthermore, the growth of both networks can be attributed to mechanisms of node duplication. Thus recent work on structural properties and evolution of the PPI network in conjunction with that of the WWW network has attracted considerable attention.
The goal of this workshop is to bring together researchers from diverse backgrounds who work on evolution and the structural properties of biological networks how these properties relate to those observed in other natural networks. The workshop will include talks on state of the art of and open questions in the following aspects of biological networks:
* Computational and experimental methods for discovering
biological networks
* Evolutionary models for biological networks and their
relationship to the models for WWW graph and other natural networks
* Combinatorial and statistical properties of biological network and their implications
* The structure of motifs and motif finding in biological networks
Leading specialists of the field will give invited presentations. There will be a poster session and we invite poster contributions.