2020年1月8日學術報告

編輯:吳秦時間:2020-01-03點擊數: 來源:  

報告題目(Title): Local and Global Network Structure of Protein-Protein Interaction Networks

報告人姓名(Speaker): Wayne B. Hayes

時間(Date&Time): 2020年1月8日上午9:30-11:30

地點(Location): 物聯網工程學院B310

報告摘要(Abstract):

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.

報告人簡介(Biography):

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


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