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DTSTAMP:20210916T132449Z
LOCATION:Jean-Jacques Rousseau
DTSTART;TZID=Europe/Stockholm:20210706T140000
DTEND;TZID=Europe/Stockholm:20210706T143000
UID:submissions.pasc-conference.org_PASC21_sess139_msa347@linklings.com
SUMMARY:The Good, the Bad, and the Ugly of Network Modeling
DESCRIPTION:Minisymposium\n\nThe Good, the Bad, and the Ugly of Network Mo
 deling\n\nClimer\n\nMany datasets are comprised of features for a set of o
 bjects, such as genetic markers for a set of individuals or weather condit
 ions for a set of climate events. A common research problem when analyzing
  such datasets is to identify combinations of objects that are intercorrel
 ated, e.g. a pattern of genetic markers that appear together for individua
 ls with Alzheimer’s disease or a pattern of weather conditions prece
 ding a tornado. These can be computed exhaustively for tiny datasets, but 
 such enumeration is intractable for most real-world data. Network modeling
  scales to massive datasets and provides high-ordered correlation patterns
  by computing pairwise relationships and building a network in which each 
 node is an object and each edge represents a correlation between the incid
 ent nodes. This presentation will provide an introduction into network mod
 eling and outline steps for researchers new to this domain while highlight
 ing underlying assumptions and potential pitfalls.\n\nDomain: CS and Math,
  Emerging Applications, Chemistry and Materials, Climate and Weather, Life
  Sciences
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