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SUMMARY:Analysing biological information processing with mechanistic modul
 ar models - Neil Dalchau\, Microsoft Research Ltd.
DTSTART:20111031T090000Z
DTEND:20111031T100000Z
UID:TALK34358@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION:Cells\, a fundamental unit of life on this planet\, are able t
 o process information deriving both from outside and within to make life-p
 reserving decisions. Molecular signals are passed within and between cells
  and generated in response to extracellular stimuli\, and feed into bioche
 mical networks that carry out the major functions of an organism: energy s
 torage\, protection from pathogens\, time-of-day determination\, etc. Unde
 rstanding biological information processing is fundamental for learning ho
 w to treat and prevent disease\, or even for using biochemistry to perform
  computation. In this talk\, I’ll show how I am using mechanistic models
  to reverse- and forward-engineer complex biochemistry\, incorporating exp
 erimental observations and exploiting modularity in the system description
 . As case studies\, I will describe my PhD work on circadian rhythms\, the
 n projects in the fields of immunology and synthetic biology that I have w
 orked on at Microsoft Research. \n\nThe immune system is a complex set of 
 mechanisms that seek to identify and rid foreign (pathogen-derived) protei
 ns\, requiring extensive information processing. I’ll introduce the firs
 t computational model of the MHC class I pathway\, which has helped to elu
 cidate how cells present a filtered snapshot of their internal contents to
  T lymphocytes (which blood cells)\, the first step in the immune system r
 ecognition of viral infection. Synthetic biology offers the potential to u
 tilise the cellular environment for functions not intended by evolution al
 one. By inserting additional DNA\, new functions/components can be conferr
 ed to cells that can be used to synthesise medicines and biofuels\, or to 
 teach us about how biochemistry facilitates information processing. I will
  show how to engineer complex spatio-temporal behaviours in populations of
  interacting bacteria\, using intercellular signalling\, inducible gene ex
 pression and a rigorous model-based design procedure.
LOCATION:Small lecture theatre\, Microsoft Research Ltd\, 7 J J Thomson Av
 enue (Off Madingley Road)\, Cambridge
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