| Date |
April 20, 2009 |
| Speaker |
Dr. See-Kiong Ng, Department Head, Institute for Incomm Research, A*STAR, Singapore |
| Title |
Unraveling the Building Blocks of Protein-Protein Interaction Networks
|
| Abstract |
Cellular processes are largely mediated by complex interactions between various proteins. As such, protein-protein interactions have been routinely determined in the laboratories for decades, culminating with the recent advent of high throughput xperimental techniques that have enabled the detection of protein interactions en masse. The availability of such large sets of interaction data, readily retrievable from public databases for an increasing number of genomes, can facilitate the discovery of new biological knowledge using novel data mining methods.
In this talk, we will present our attempts to discover the potential building blocks of protein-protein interactions by unraveling the
possible common denominators of protein interaction networks at the submolecular level (domain-domain and linear motif interactions) as well as the subgraph level (network motifs). We will show how the protein-protein interaction network can be a rich source of computationally challenging problems for the computer scientists and a gold mine of biologically interesting knowledge for the biologists.
|
| Biography |
See-Kiong Ng is currently the Department Head of the Data Mining Department at the Institute for Infocomm Research. He is also an adjunct Associate Professor at the School of Computer Engineering, Nanyang Technological University. See-Kiong obtained his Bachelor, Masters, and Ph.D. degrees in Computer Science from Carnegie Mellon University.
Prior to joining the Institute of Infocomm Research in Singapore in 2000, See-Kiong has worked internationally: as a post-doc in Tomita's Lab in Keio University Japan, a senior scientist in Smithkline Beecham Pharmaceutical in England, and a principal scientist in the biotech start-up DNA Sciences in the silicon valley of the USA. See-Kiong's current research focuses on unraveling the underlying functional mechanisms of protein interaction networks as well as other real-world networks, such as the social networks of researchers. His diverse and cross-disciplinary research interests includes Bioinformatics, Text Mining, Network Mining, and most recently, Privacy-Preserving Data Mining.
|
|
アブストラクト