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SUMMARY:Predictive Modeling Approaches to Gene Regulation - Jun Liu (Harva
 rd University)
DTSTART:20080305T140000Z
DTEND:20080305T150000Z
UID:TALK11023@talks.cam.ac.uk
CONTACT:8419
DESCRIPTION:Transcription factors regulate gene expression through their b
 inding to target DNA sequences. With the help of motif finding\, we can pr
 edict transcription factor binding sites and thus decode the regulatory ne
 twork. The adoption of large-scale biological data generation techniques s
 uch as the mRNA microarrays has enabled researchers to tackle the gene reg
 ulation problem in a global way. We will describe some computational and s
 tatistical strategies developed by our group for combining the gene upstre
 am sequence information with mRNA expression microarray data to dissect th
 e gene regulatory network. \nWe term this type of methods "predictive mode
 ling approaches" because they take the expression data (or other gene-leve
 l quantitative measurements) as the response variable and attempt to use s
 equence information to predict the response. Main advantages of these appr
 oached are: (a) they are much more sensitive and specific than those seque
 nce-only motif-discovery approaches when the motif signal is weak\; (b) ma
 ny advanced statistical learning tools can be used and various sophisticat
 ed dimension reduction and variable selection techniques can be applied un
 der this coherent framework\; (c) the discovered motifs or other sequence 
 patterns can be "statistically" confirmed by cross-validations instead of 
 relying purely on previous biological knowledge or further follow-up exper
 iments. \n\nWe first demonstrate a re-analysis of the dataset from Beer an
 d Tavazoie (2004)\, which serves to warn against "over-interpretation" whe
 n a pedictive mdoeling approach is used. Then we describe some successful 
 applications of the methods\, such as statistical analyses of histone modi
 fication and nucleosome occupancy data. If time permit\, I will also discu
 ss some related statistical problems. \n\n
LOCATION:MR12\, CMS\, Wilberforce Road\, Cambridge\, CB3 0WB
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