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SUMMARY:Programming Cells: Computing with DNA - Dr. Neil Dalchau\, Microso
 ft Research 
DTSTART:20130125T140000Z
DTEND:20130125T153000Z
UID:TALK41562@talks.cam.ac.uk
CONTACT:Dr Jason Z JIANG
DESCRIPTION:The ability to reliably re-program cells has great potential f
 or tackling societal challenges\, in areas such as health\, food and energ
 y. DNA is the code that stores the information required to replicate life\
 , and is read by cellular machinery. In addition to its role in the natura
 l sense\, it is also possible to use DNA as a substrate for computing\, by
  taking advantage of its physical properties. Such DNA computing offers an
  exciting potential to perform complex calculations within the cellular en
 vironment\, and interface to the natural machinery of the cell to perform 
 conditional actions. In this talk\, I’ll show how we have used DNA stran
 d displacement to create complex dynamical behaviours. The network design 
 benefits from the Visual DSD software\, developed by ourselves\, to build\
 , analyse and test models of DNA strand displacement networks. We formally
  implement chemical reaction networks (CRNs)\, which are capable of a rich
  set of nonlinear dynamics. By combining DNA implementations of non-cataly
 tic and autocatalytic reactions\, we construct a circuit that implements t
 he approximate majority algorithm\, the fastest way for a population to re
 ach a collective majority decision between two possible outcomes. The expe
 rimentally observed dynamics of the full circuit are well predicted by a m
 odel whose parameters are inferred from experimental measurements of the c
 onstituent reactions using Markov chain Monte Carlo parameter estimation.
LOCATION: Cambridge University Engineering Department\, Lecture Room 3B
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