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SUMMARY:Orthologous networks in biological systems - Dr Christopher Penfol
 d (Warwick)
DTSTART:20150211T110000Z
DTEND:20150211T120000Z
UID:TALK57974@talks.cam.ac.uk
CONTACT:Zoubin Ghahramani
DESCRIPTION:How an organism develops and responds to environmental stress 
 is influenced by its gene regulatory network (GRN). Here I outline nonpara
 metric Bayesian approaches to network inference based upon Gaussian proces
 ses\, that allows networks to be inferred from multiple time series transc
 riptomic datasets. These approaches have proven to be highly successful at
  identifying important regulators in a variety of processes in Arabidopsis
  thaliana. Furthermore\, these methods address another key challenge in ne
 twork inference: how to infer networks from multiple datasets when the und
 erlying networks are expected to be similar\, but non-identical. This may 
 be the case when networks are rewired in different treatments (treatment s
 pecific networks)\, where network differences arise due to genetic differe
 nces (individual or patient specific networks) and (iii) where data is col
 lected in different but related species.
LOCATION:Engineering Department\, CBL Room BE-438.
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