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SUMMARY:Information processing in small gene regulatory networks and casca
 des - Aleksandra Walczak\, Centre for Theoretical Science\, Princeton
DTSTART:20091109T110000Z
DTEND:20091109T113000Z
UID:TALK21142@talks.cam.ac.uk
CONTACT:Duncan Simpson
DESCRIPTION:Many of the biological networks inside cells can be thought of
  as transmitting information from the inputs (e.g.\, the concentrations of
  transcription factors or other signaling molecules) to their outputs (e.g
 .\, the expression levels of various genes). On the molecular level\, the 
 relatively small concentrations of the relevant molecules and the intrinsi
 c randomness of chemical reactions provide sources of noise that set physi
 cal limits on this information transmission. Given these limits\, not all 
 networks perform equally well\, and maximizing information transmission pr
 ovides a optimization principle from which we might hope to derive the pro
 perties of real regulatory networks. I will discuss the properties of spec
 ific small networks that can transmit the maximum information. Concretely\
 , I will show how the form of molecular noise drives predictions not just 
 of the qualitative network topology but also the quantitative parameters f
 or the input/output relations at the nodes of the network. In an attempt t
 o link these general theoretical considerations to real biological systems
 \, I will illustrate the predictions on the example of transmission of pos
 itional information in the early development of the fly embryo. Lastly\, I
  will discuss different approaches of how a stochastic molecular level des
 cription can be successfully expanded to larger regulatory systems.\n\nhtt
 p://www.physics.princeton.edu/pctp/people/walczak_aleksandra.html
LOCATION:Seminar Room\, Centre for Physics of Medicine (PoM)
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