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TZID:America/Chicago
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DTSTART:20210314T030000
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DTSTART:20211107T010000
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BEGIN:VEVENT
DTSTAMP;TZID=America/Chicago:20260417T222843
UID:163353@calendar.wisc.edu
DTSTART;TZID=America/Chicago:20211015T120000
DTEND;TZID=America/Chicago:20211015T130000
DESCRIPTION:Department of Biostatistics and Medical Informatics Seminar. Dr
 . Sara Mostafavi will present machine learning approaches recently develop
 ed by her lab for leveraging heterogeneous data and prior knowledge to gui
 de discovery of meaningful biological structure. In particular\, she will 
 first describe her deep learning approach (AI-TAC) to combining a large co
 mpendium of epigenomic data\, in order to learn the relationship between n
 on-coding sequence and regulatory activity across the immune system.\n\nCO
 NTACT: clindstrom@biostat.wisc.edu\n\nONLINE: https://uwmadison.zoom.us/j/
 93316332486?pwd=YXJ1T1NEK3Z0N1ZXKzFNNGNnTVU1Zz09
LOCATION:  (Online)
SUMMARY:Machine learning as an assay for high-dimensional biology
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