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SUMMARY:Identifying novel therapies for breast cancer using Independent Co
 mponent Analysis - Andrew E Teschendorff (Cancer Research Institute\, Univ
 ersity of Cambridge)
DTSTART:20070207T140000Z
DTEND:20070207T150000Z
UID:TALK6615@talks.cam.ac.uk
CONTACT:Danielle Stretch
DESCRIPTION:Most standard methods for analysing tumour-derived gene expres
 sion data do \nnot attempt to explicitly infer the altered biological proc
 esses underlying \ncancer. By viewing gene expression as a blind source se
 paration (BSS) \nproblem we can characterise the inferred biological proce
 sses in terms of \naberrations in functional pathways and transcriptional 
 programs. Using \nIndependent Component Analysis (ICA) to perform BSS\, we
  show that ICA \nsignificantly outperforms other linear decomposition tech
 niques. We \ndescribe the application of ICA in a meta-analysis of breast 
 cancer\, \nleading to novel associations between biological pathways\, reg
 ulatory \nmodules and breast cancer phenotypes.
LOCATION:MR5\, DAMTP
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