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BEGIN:VEVENT
DTSTAMP:20261017T214210Z
LAST-MODIFIED:20191210T153916Z
DTSTART:20191211T170000Z
DTEND:20191211T180000Z
UID:event2251@bu.edu
URL:http://physics.bu.edu/internal/events/show/2251
SUMMARY:Student Seminar Series
DESCRIPTION:Featuring Ashish George\, Boston University\nHosted by: Eric Bo
	yers\n\nPart of the Graduate Student Council Events.\n\nAshish George (BU\,
	 Bio Theory)\nEco-evolutionary dynamics of complex microbial populations wi
	th heterogeneous growth and dispersal\n\nFor continued survival in a spatia
	l habitat\, all organisms must migrate to new territories and reproduce. Th
	e interplay of these two fundamental processes—migration and reproduction
	—determines the outcome of species invasions\, growth of cancer tumors\, 
	and stability of complex microbial communities. Understanding and controlli
	ng these systems requires ecosystem models that appropriately account for p
	opulation heterogeneity. In this talk\, I will describe three such modeling
	 efforts in increasing order of population heterogeneity. First\, I will de
	scribe a minimal model incorporating chiral bias in migration that quantita
	tively reproduces experimental patterns in bacterial colonies. Using this m
	odel\, I demonstrate chirality can provide an evolutionary fitness advantag
	e\, and differences in cellular chirality can impact cancer invasion and sp
	ecies coexistence. I will present a general effective theory of chiral grow
	th to explain the selection mechanism favoring chiral cells. Second\, I des
	cribe a model of a growing bacterial colony composed of two sub-populations
	 with distinct growth and migration strategies. I show how coordination in 
	a cooperative population reproduces concentric rings and periodic boundary 
	motion observed in P. mirabilis colonies\, and discuss the implied evolutio
	nary tradeoffs between exploration and exploitation. Finally\, for populati
	ons of many heterogeneous interacting species\, I study the process of asse
	mbling an optimal microbial community performing a desired function such as
	 biofuel production\, waste degradation\, or disease treatment. I show that
	 the difficulty of searching for the optimal community is determined by the
	 structure of the "landscape" of community function.
LOCATION:SCI 328\, 590 Commonwealth Avenue\, 02215
STATUS:CONFIRMED
CLASS:PUBLIC
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