Wednesday, Oct 22nd, 2008; Liivi 2-403
Leopold Parts -- http://www.sanger.ac.uk/Users/lp2/
Bayesian model for gene expression.
Gene expression is the most basic phenotype that directly influences the biology of the cell. We can measure the expression levels of thousands of genes at a time - the problem is understanding the signal in the data. I'll present a Bayesian model for finding the determinants of gene expression, and the variational strategy for learnings it. Application of this model to real data has shown significant improvements in sensitivity - we find common genetic variation controlling expression of every gene.
Thursday, July 3rd, at 3:15pm, Liivi 2-317 (Inst. of Computer Science)
Title: Gene Expression-Based Glioma Classification Using Hierarchical
Bayesian Kernel Machine Models
Everybody is welcome!