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X-ORIGINAL-URL:https://archive.renci.org
X-WR-CALDESC:Events for RENCI
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DTSTART:20180311T070000
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DTSTART:20181104T060000
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DTSTART;TZID=America/New_York:20180626T080000
DTEND;TZID=America/New_York:20180626T170000
DTSTAMP:20260412T225211
CREATED:20180626T142542Z
LAST-MODIFIED:20180626T142542Z
UID:17576-1530000000-1530032400@archive.renci.org
SUMMARY:Combining machine learning and population genetics to elucidate evolutionary histories
DESCRIPTION:Invited Speaker \nProf. Dan Schrider \nDescription \nGenome sequence data can be used to answer a host of questions about evolutionary history. To what extent is genetic variation shaped by natural selection and recombination? Has a population experienced substantial changes in size? To what extent has there been gene flow between populations? In recent decades theoretical and methodological advances in population genetics have sought to address each of these questions. In this talk I will describe my efforts adapting supervised machine learning methods to answer evolutionary questions. I will demonstrate that these approaches outperform more traditional modes of population genetic inference\, and yield valuable insights about recent evolutionary history including the process of recent and ongoing adaptation in human populations.
URL:https://archive.renci.org/event/combining-machine-learning-and-population-genetics-to-elucidate-evolutionary-histories/
LOCATION:Fishbowl Conference ROom
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