Inference of Protein Structure and Function
Speaker: Michael Jordan , University of California, BerkeleyContact:
Date: May 5 2011
Time: 4:00PM to 5:00PM
Host: David Gifford & Tommi Jaakola, CSAIL
Colleen Russell, 3-0145, email@example.comRelevant URL:
The study of the structure and function of proteins raises many
problems that offer challenges and opportunities for computational
and statistical research. I will overview my experiences in several
such problem domains, ranging from domains where off-the-shelf ideas
can be fruitfully applied to domains that require new thinking.
These are: (1) the identification of active sites in enzymes;
(2) the modeling of protein backbone configurations; (3) the prediction
of molecular function based on phylogeny; (4) joint inference of alignment
Michael I. Jordan is the Pehong Chen Distinguished Professor in the
Department of Electrical Engineering and Computer Science and the
Department of Statistics at the University of California, Berkeley.
His research in recent years has focused on Bayesian nonparametric
analysis, probabilistic graphical models, spectral methods, kernel
machines and applications to problems in statistical genetics,
computational biology, signal processing, information retrieval and
natural language processing. Prof. Jordan has been named as a Neyman
Lecturer and a Medallion Lecturer by the Institute of Mathematical
Statistics (IMS). He has received the ACM/AAAI Allen Newell Award in
2009, the SIAM Activity Group on Optimization Prize in 2008, and the
IEEE Neural Networks Pioneer Award in 2006. He is a Fellow of the
American Association for the Advancement of Science, a Fellow of the
IMS, a Fellow of the IEEE, a Fellow of the AAAI and a Fellow of the ASA.
In 2010, Prof. Jordan was named to the National Academy of Engineering
and the National Academy of Sciences.
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