|
CoNe Lab is developing graph theoretic and computational approaches for network mining, i.e., analyzing, modeling, clustering, and comparing (i.e., aligning) large real-world networks to enable efficient extraction of functional information from network structure (or topology). One of our primary focuses is on computational and systems biology, i.e., applying our methods to biological networks, e.g., networks of interactions between proteins in the cell, to address many important problems in biomedicine, such as predicting protein function or identifying novel disease genes and drug targets. Efficient extraction of meaningful functional information from biological networks could yield valuable insights into complex biological mechanisms in the cell and deepen our understanding of biological function, disease, and evolution. In addition, we are interested in applying the methods to other types of real-world networks, such as social networks – networks of friendships and acquaintances or on-line social communities, or technological networks, such as the Internet.
|