報告題目(Title): Local and Global Network Structure of Protein-Protein Interaction Networks
報告人姓名(Speaker): Wayne B. Hayes
No protein is an island unto itself, because its function is intimately tied to its set of interaction partners. Since proteins come from genes, and closely-related species exhibit high genetic similarity, we expect that orthologous proteins between species share similar interaction partners. These observations underlie the assumption that the protein-protein interaction networks of many species share similar network connection topology. Conversely, since there are known examples of functional similarity in the absence of sequence similarity, and since a protein's function is effectively defined by the network topology in which it is embedded, analysis of network topology holds the promise of discovering novel functional relationships that cannot be inferred by sequence analysis. Our lab uses several sophisticated graph theory techniques both to test these statements, and to glean new biological insights into protein function.
Hayes is an associate professor in the department of computer science at University of California, Irvine. He is also the associate director of UCI Center for Computational Morphodynamics. He completed his PhD in computer science at the University of Toronto in 2001. His current research interests include complex systems, computational biology, machine learning, algorithms and computer systems.
邀請人 (Inviter): 陳璟