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UID:20250629T100140EDT-7654BLolmG@132.216.98.100
DTSTAMP:20250629T140140Z
DESCRIPTION:Learning from Life: Lessons from ML and Biophysical Simulations
\n\nRe Mansbach\, Concordia University\n Tuesday January 7\, 12-1pm\n Zoom L
ink:聽https://mcgill.zoom.us/j/89914150820\n In Person: 550 Sherbrooke\, Roo
m 189\n \n Abstract:聽Proteins and peptides are the molecular motors that kee
p our cells running. Many of them can be used as drug targets or biomolecu
lar drugs for therapeutic applications\, but the search space of the possi
ble amino acid combinations forming even a short peptide is astronomical.
To design new peptides for specific applications\, we need a larger-scale
understanding of the entire search space. In my lab\, we address these que
stions through a combination of interpretable machine learning and optimiz
ation techniques to rationally explore ML-associated search spaces for pep
tides and the parameterization and application of simulations to understan
d candidates of particular interest at a detailed molecular level. In this
presentation\, I will introduce the tools of our trade and discuss how we
apply them to some of our ongoing projects\, with a particular focus on a
ntimicrobial peptide understanding and design.\n
DTSTART:20250107T170000Z
DTEND:20250107T180000Z
SUMMARY:QLS Seminar Series - Re Mansbach
URL:/qls/channels/event/qls-seminar-series-re-mansbach
-361384
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