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SUMMARY:Algorithmic Investigation of Large Biological Data sets - Lee Clew
 ley\, GSK
DTSTART:20180227T130000Z
DTEND:20180227T140000Z
UID:TALK100813@talks.cam.ac.uk
CONTACT:Dr Vivien Gruar
DESCRIPTION:Recently the rapid growth of both internal and external data s
 ources in conjunction with large external databases has increased the need
  for GSK to address the most complex problems in drug discovery. For examp
 le\, the chemical database ChEMBL\, coupled with various biological databa
 ses internal and external to GSK with have meant that there is presently a
 n enormous set potential set of research avenues that will yield biologica
 lly interesting insights. Such datasets provide a rich environment for dep
 loyment of algorithms such as Tensor flow\, Deepchem or Topological Data A
 nalysis depending on the form of the data. \n\nIn this project\, the stude
 nt will explore and create several algorithms that will be applied to cura
 ted datasets to test a range of biological hypothesis. This project is rel
 atively open-ended and so the student should be ready to explore and evalu
 ate current academic work and applicable solutions. The student should be 
 prepared to collaboratively suggest viable hypothesis based on the data at
  hand.  \n\nThe student should also be prepared\, with aid from supervisor
 s and contacts within the company\, to demonstrate their findings in the f
 orm of visualizations\, code-based models\, or another appropriate medium.
 \n\n
LOCATION:MR3 Centre for Mathematical Sciences
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