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X-WR-CALNAME:AND/OR Branch-and-Bound for Computational Protein Design Optim
izing K*
X-WR-TIMEZONE:America/Los_Angeles
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DTSTART:20070311T020000
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UID:2022-06-06-bobak-pezeshki@cml.ics.uci.edu
DTSTAMP:20220606T000000Z
SEQUENCE:57690
DTSTART;TZID=America/Los_Angeles:20220606T130000
DTEND;TZID=America/Los_Angeles:20220606T140000
SUMMARY:[CML Seminar] Bobak Pezeshki: AND/OR Branch-and-Bound for Computati
onal Protein Design Optimizing K*
LOCATION:Donald Bren Hall 4011
DESCRIPTION:Bobak Pezeshki\, PhD Student\, Department of Computer Science\,
University of California\, Irvine\n\nTitle: AND/OR Branch-and-Bound for C
omputational Protein Design Optimizing K*\n\nAbstract: Computational prote
in design (CPD) is the task of creating new proteins to fulfill a desired
function. In this talk\, I share work accepted at UAI 2022 based on a new
formulation of CPD as a graphical model designed for optimizing subunit bi
nding affinity (approximated by a quantity called K*). I relate this to th
e task of MMAP\, present the formulation of the problem as a graphical mod
el\, and introduce a weighted mini-bucket heuristic for bounding K* and gu
iding search. Finally\, I share our algorithm AOBB-K* and modifications th
at enhance it\, describing its empirical benefits and limitations.\n\nhttp
s://cml.ics.uci.edu/seminars/2022-06-06-bobak-pezeshki
X-ALT-DESC;FMTTYPE=text/html:Bobak Pezeshki\, PhD Studen
t\, Department of Computer Science\, University of California\, Irvine
Title: AND/OR Branch-and-Bound for Computational Protein Design
Optimizing K*
Abstract: Computational protein design (CPD)
is the task of creating new proteins to fulfill a desired function. In thi
s talk\, I share work accepted at UAI 2022 based on a new formulation of C
PD as a graphical model designed for optimizing subunit binding affinity (
approximated by a quantity called K*). I relate this to the task of MMAP\,
present the formulation of the problem as a graphical model\, and introdu
ce a weighted mini-bucket heuristic for bounding K* and guiding search. Fi
nally\, I share our algorithm AOBB-K* and modifications that enhance it\,
describing its empirical benefits and limitations.
https://cml.ics.uci.e
du/seminars/2022-06-06-bobak-pezeshki
URL:https://cml.ics.uci.edu/seminars/2022-06-06-bobak-pezeshki
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