BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:A Bayesian model that links microarray mRNA measurements to mass s
 pectrometry protein measurements - Anitha Kannan\, Microsoft Research\, Ca
 mbridge
DTSTART:20070410T140000Z
DTEND:20070410T150000Z
UID:TALK7073@talks.cam.ac.uk
CONTACT:Oliver Williams
DESCRIPTION:An important problem in biology is to understand correspondenc
 es between mRNA microarray levels and mass spectrometry peptide counts. Re
 cently\, a compendium of mRNA expression levels and protein abundances wer
 e released for the entire genome of the laboratory mouse\, Mus musculus. T
 he availability of these two data sets facilitate using machine learning m
 ethods to automatically infer plausible correspondences between the gene p
 roducts. Knowing these correspondences can be helpful either for predictin
 g protein abundances from microarray data or as an independent source of i
 nformation that can be used for learning richer models such as regulatory 
 networks. In this talk\, we present a probabilistic model that relates pro
 tein abundances to mRNA expression levels. Using cross-mapped data from th
 e above-mentioned studies\, we learn the model and then score the genes fo
 r their strength of relationship by performing probabilistic inference in 
 the learned model. We demonstrate that the Bayesian technique achieves map
 pings with higher statistical significance\, compared to standard linear r
 egression and a maximum likelihood version of the proposed model. \n \nThi
 s work is done in collaboration with Brendan Frey and Andrew Emili\, Unive
 rsity of Toronto 
LOCATION:Small public lecture room\, Microsoft Research Ltd\, 7 J J Thomso
 n Avenue (Off Madingley Road)\, Cambridge
END:VEVENT
END:VCALENDAR