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VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
BEGIN:VEVENT
DTSTAMP:20260808T163853Z
UID:f9ebfc1a-bc63-4049-9dfb-f338b2fec859
DTSTART:20170524T090000Z
DTEND:20170524T000000Z
DESCRIPTION:Current pharmaceutical research and development generates vast 
 amounts of data. These big data come from high content screens\, magnetic 
 resonance imaging\, omics and diagnostic patient monitoring devices. Toget
 her with this increasing magnitude of databases there is an associated inc
 rease in the time required to execute data processing. With the increasing
  complexity of methodology and new scientific insights\, the existing comp
 utational algorithms and infrastructure are unlikely to cope with the chal
 lenges soon. Complex statistical models will push the limits of the curren
 t algorithms and implementations. To be able to face the challenges of the
  near future increased performance both at the algorithmic and software/ha
 rdware levels are deemed crucial.\n Case studies on drug development will 
 be given. One important project that is part of a collaboration of academi
 c and industrial partners is conducting research on the computational requ
 irements for disease modeling of Type II Diabetes as part of the ExaScienc
 e project (www.exascience.com). Appropriate use of computing infrastructur
 e and high performance computing software makes it possible to use these n
 ew technologies in a time-constrained setting. This is a requirement when 
 the disease models are used to make decisions within hours during the inte
 rim analyses of clinical trials with adaptive experimental designs. Beside
 s this project other real-life cases presented include genomics\, microbio
 me and brain imaging.\n Speaker: Luc Bijnens PhD\, Janssen Pharmaceutical 
 Companies of Johnson and Johnson\, 30 Turnhoutseweg\,\n

LOCATION:Hasselt University room C20 building D
SUMMARY:Big data and High Performance Computing in Life Sciences
URL;VALUE=URI:https://www.vscentrum.be/en/education-and-trainings/detail/da
 ta-science--life-sciences-24052017
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