We have an exciting line-up of keynote speakers:

• Ken Dill, University of California at San Francisco
• Michael Levitt, Stanford University
• Terry Speed, University of California at Berkeley and WEHI, Melbourne, Australia.

 

---

 

Protein Folding Physics and its Application to Protein Structure Prediction

 

Ken Dill, Professor of Biophysics and Pharmaceutical Chemistry and Associate Dean of Research, University of California at San Francisco

 

9:00am, Saturday, February 23, 2008

 

Abstract We have been interested in the physical principles of protein folding -- the nature of the folding code, the mechanisms by which proteins fold up so quickly, and the origins of folding cooperativity, for example. These questions can be explored using simplified physical models. Work on the folding code has led to new molecules, called foldamers, that are now finding applications in biomedicine. Work on protein folding kinetics has led to a mechanism called zipping and assembly, that has recently found to be useful to speed up physics-based computer methods for predicting protein structures.

 

Biography Ken Dill received SB and SM degrees from the MIT Mechanical Engineering Department, his PhD in Biology at UCSD, and did postdoctoral work in Chemistry at Stanford. He has been at UCSF since 1983, where he is currently Professor of Biophysics and Pharmaceutical Chemistry and an Associate Dean of Research. His research has been at the intersection between statistical thermodynamics and biomolecules, and includes interests in protein and RNA folding, the properties of water, and the nonequilibrium properties of small systems. He has co-authored a textbook, called Molecular Driving Forces. He received the Hans Neurath Award from the Protein Society in 1998, has been the President of the Biophysical Society, and received the 2007 Distinguished Service Award from the Biophysical Society for his role in passing federal legislation to help in bridging between the life and physical sciences.

 

---

 

Mesoscale Modeling of Macromolecular Machines

 

Michael Levitt, Professor and Chair of Structural Biology, Stanford University

 

9:00am, Friday, February 22, 2008

 

Abstract This talk will cover the work of some members of the Levitt Lab all directed towards large-scale modeling of mesoscale modeling of macromolecular machines. My own work, described first, will focus an approach specially designed to model the structure and dynamics of large macromolecular nano-machinery. The description of the others^Y work will start with that if Dahlia Weiss on the solvation of a carbon nano-sphere, will continue with low-resolution explorations of protein fold space done by Dr. Peter Minary before ending with a novel method of deforming molecular structures to fit electron density at various resolutions by Dr. Gunnar Schroeder.

 

Biography Born in South Africa, educated in England (London for Physics and Cambridge for MRC Laboratory of Molecular Biology), Michael Levitt has held tenured academic positions in England (Cambridge), Israel (Weizmann Institute) and the US (Stanford) while enjoying numerous short academic visits around the world. He was a founders of computational structural biology. Starting in 1967, he programmed the first empirical force-field and ran the first all-atom minimizations of entire proteins, an essential precursor of the molecular dynamics that became possible as computer time increased. With Warshel he introduced a continuum implicit solvent model used with protein simulations that also included quantum terms so introducing QM/MM simulations decades before they became popular. He and Warshel also introduced simplified or reduced model for proteins now used commonly in simulation of folding. Levitt and Chothia co-discovered the four classes of proteins architecture and the rules for packing secondary structure segments that are still valid today. More recently he did the first realistic simulations of protein dynamics in explicit water using a protocol that is widely adopted. His decoy and discriminate paradigm of protein structure predicting is also generally used. Michael Levitt heads the Computational Structural Biology group at Stanford, where about a dozen students and postdocs tackle a wide variety of problems in the field. He continues to write programs and do his own research, most recently focused on determining the size of the protein universe and also calculating proper normal modes of proteins in torsion angle space.

 

---

 

Alternative Splicing in Tumors: Detection and Interpretation

 

Terry Speed, Professor of Statistics, University of California at Berkeley and Head of Bioinformatics Division, Walter & Eliza Hall Institute of Medical Research (WEHI), Melbourne, Australia.

 

1:30pm, Friday, February 22, 2008

 

Abstract In this talk I will discuss using the Affymetrix GeneChip? Human Exon and Human Gene 1.0 ST arrays for the detection of genes spliced differently in some tumors in comparison with others. I plan to begin by introducing the arrays and the expression data they produce. Next I will outline the way in which we use such data in our attempts to identify exon-tumor combinations exhibiting splicing patterns different from the majority. This will be illustrated by examples from publicly available tissue and mixture data. Then I will briefly discuss some of the additional issues which arise when we seek to enumerate such alternative splicing patterns on a genome-wide scale. Finally, I will exhibit some of the results we have found applying these methods to glioblastoma tissue samples collected as part of The Cancer Genome Atlas (TCGA) project. (This is joint work with ELizabeth Purdom, Mark Robinson, Ken Simpson, and members of the Berkeley Cancer Genome Center.)

 

Biography Terry Speed splits his time between the Department of Statistics at the University of California, Berkeley and the Walter & Eliza Hall Institute of Medical Research (WEHI) in Melbourne, Australia. Originally trained in mathematics and statistics, he has had a life-long interest in genetics. After teaching mathematics and statistics in universities in Australia and the United Kingdom, and a spell in Australia's Commonwealth Scientific and Industrial Research Organization, he went to Berkeley 21 years ago. Since that time, his research and teaching interests have concerned the application of statistics to genetics and molecular biology. Within that subfield, eventually to be named bioinformatics, his interests are broad, including biomolecular sequence analysis, the mapping of genes in experimental animals and humans, and functional genomics. He has been particularly involved in the low level analysis of microarray data. Ten years ago he took the WEHI job, and now spends half of his time there, half in Berkeley, and the remaining half in the air somewhere in between.

 

---