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DTSTAMP:20190719T085745Z
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DTSTART;TZID=Europe/Stockholm:20190614T133000
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UID:submissions.pasc-conference.org_PASC19_sess149_msa325@linklings.com
SUMMARY:Subtle Characteristics of Clustering Algorithms
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Emerg
 ing Application Domains, Climate and Weather, Life Sciences\n\nSubtle Char
 acteristics of Clustering Algorithms\n\nClimer\n\nEven though they are fre
 quently arbitrarily employed, clustering algorithms are widely diverse and
  carry underlying characteristics that may dramatically impact results. Wh
 en multiple methods are employed, the results can vary radically and it fr
 equently is difficult to objectively measure the most meaningful outcome a
 nd select a reliable approach. Moreover, many algorithms are computational
 ly expensive, and researchers frequently prune their networks in a pre-pro
 cessing step, risking the loss of critical information. Such a predicament
  wastes valuable resources and hinders scientific progress. This presentat
 ion will delve into these issues and utilize networks produced in the stud
 y of genetic associations with complex traits to demonstrate the pressing 
 needs in this field.
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