Comparative Analysis of Biological Networks

Recent developments in molecular biology have§resulted in experimental data that§entails the relationships and interactions between§biomolecules. Biomolecular interaction§data, generally referred to as biological or cellular§networks, are frequently§abstracted using graph models. In systems biology,§comparative analysis of these§networks provides understanding of functional§modularity in the cell by integrating§cellular organization, functional hierarchy, and§evolutionary conservation. In this§study, we address a number of algorithmic issues§associated with comparative§analysis of molecular interaction networks. We first§discuss the problem of identifying common§sub-networks in a collection of molecular interaction§networks belonging to diverse species. With a view to§understanding the conservation and divergence of§functional modules,§we also develop network alignment techniques,§grounded in theoretical models of network evolution.§Finally, we probabilistically analyze the existence§of highly connected and conserved subgraphs§in random graphs, in order to assess the statistical§significance of the patterns identified by our§algorithms.