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DTSTAMP:20261018T193031Z
LAST-MODIFIED:20180831T162913Z
DTSTART:20180904T190000Z
DTEND:20180904T200000Z
UID:event2011@bu.edu
URL:http://physics.bu.edu/internal/events/show/2011
SUMMARY:Statistical Physics of Information Processing by Cells
DESCRIPTION:Featuring Ching-Hao Wang\n\nPart of the Departmental Seminars.\
	n\nDissertation Committee:  Pankaj Mehta\, Kirill Korolev\, Claudio Chamon\
	, Andrew Liam Fitzpatrick\, Allyson Sgro\n\nAbstract:\n\nEukaryotic cells t
	ransmit information using complex biochemical signaling networks based on\n
	protein-protein interactions (PPIs). In this talk\, I'll discuss a theoreti
	cal and computational\nframework I developed which relates network-level in
	formation processing properties to the\nbiophysical properties of PPIs. To 
	do so\, I first generalize statistical physics-inspired models for\nprotein
	 binding to account for post-translational modifications (PTMs) of proteins
	 (e.g.\,\nphosphorylation) and PTM-dependent binding\, both of which are es
	sential characteristics of\nsignaling. By combining these models with infor
	mation theoretic methods\, I’ll show that the\nstrength of PPIs acts as a
	 regulator of information transmission: weak PPIs give rise to "noise"\ntha
	t limits information transmission and that such noise mediates a fundamenta
	l trade-off\nbetween speed of dynamical response and information. I’ll al
	so discuss a surprising finding that\ncross-talks between pathways in compl
	ex signaling networks do not significantly alter\ninformation capacity\, an
	 observation that may partially help explain the promiscuity and ubiquity\n
	of weak PPIs in naturally-occurring signaling networks. Finally\, I’ll co
	nclude by showing how these\nideas can be used to design PPIs in synthetic 
	biochemical networks to maximize information\ntransmission\, a procedure we
	 dub "InfoMax" design.
LOCATION:SCI 328\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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