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SUMMARY:Exploring Chemical Space with Random Matrix Theory - Dr Alpha Lee\
 , University of Cambridge
DTSTART:20171116T141500Z
DTEND:20171116T151500Z
UID:TALK84711@talks.cam.ac.uk
CONTACT:Bartomeu Monserrat
DESCRIPTION:Developing computational methods to explore chemical space is 
 a major challenge for drug discovery and material discovery. The challenge
  is often the limited number of experimental measurements relative to the 
 vast chemical space. I will discuss a mathematical framework\, inspired by
  random matrix theory\, which allows us to remove noise due to finite samp
 ling and identify important chemical features. I will illustrate this fram
 ework with three examples: predicting protein-ligand affinity\, optimal de
 sign of experiments by combining coarse and fine measurements\, and inferr
 ing a probabilistic generative model by combining liquid state theory with
  deep learning. 
LOCATION:TCM Seminar Room\, Cavendish Laboratory
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