College of Liberal Arts & Sciences

Extracting hidden information from large-scale biological networks by optimal community detection

Wednesday, November 7, 2012

November 7, Wed 2012
2:00 pm, MRB 200 Conference Room

Dr. Jooyoung Lee

Center for In Silico Protein Science, Korea Institute for Advanced Study

Extracting hidden information from large-scale biological networks by optimal community detection

Currently, we are overwhelmed by a deluge of data, and network science has the potential to become an invaluable method to increase our understanding of large interacting datasets. However, this potential is often unrealized for two reasons: uncovering the hidden community structure—known as community detection— is difficult, and even if one has an idea of this community structure, it is a priori not obvious how to use this information. Here, we investigate three large-scale biological networks, where optimal community detection leads to the discovery of additional biological information hidden in the network. Networks studied here include the yeast protein-protein interaction network, the yeast protein-complex network, and a protein-carbohydrate network constructed from lectin-glycan microarrays. For each network, the performance of our method will be compared with existing state-of-the-arts methods in both the mathematical optimality of the partitioning as well as the usefulness of the clustering in terms of biological implications.



One of 34 U.S. public institutions in the prestigious Association of American Universities
44 nationally ranked graduate programs.
—U.S. News & World Report
Top 50 nationwide for size of library collection.
—ALA
23rd nationwide for service to veterans —"Best for Vets," Military Times
KU Today