Thursday, October 10, 2013 - 10:15am - 11:05am
Monica Nicolau (Stanford University)
I will discuss the effect of geometric transformations on the topology of data. Geometric transformations are central in highlighting characteristics in the data that extract information. A common feature is that the same data set can provide answers to multiple problems. Thus the choice of underlying geometry is crucial in highlighting the answers to the correct problem. There will be many examples from systems biology.
Monday, January 14, 2008 - 10:25am - 10:55am
Christodoulos Floudas (Princeton University)
Joint work with S. R. McAllister.

The protein folding question has developed over the past four decades as one of the most challenging and potentially rewarding problems in computational biology. Three general classes of algorithms have emerged, based on the techniques of comparative
modeling, fold recognition, and first principles methods. For a detailed summary of protein structure prediction methods, the reader


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