^June July – 2009 ^August

Alternative splicing (AS) is an RNA processing mechanism creating protein diversity in higher eukaryotes. It is regulated by splicing factors that interact with their binding sites along exons and introns. One of the main challenges in the study of AS regulation is to accurately map splicing factor binding motifs on the RNA. Therefore we developed a new method for mapping binding sites of known splicing factors which considers both the genomic environment of a single binding site and the evolutionary conservation of these sequences. The method was successfully applied to map splicing factor binding sites on specific genes and also on a wide genomic scale. By applying the algorithm on a subset of splicing factors we constructed a splicing regulatory network. This network presented a hierarchical structure that correlated with the tissue specificity levels of the splicing factors. Further to study the relationship between splicing factors and transcription regulation we derived a transcription-splicing co-regulatory network, where the nodes of the network are the Splicing Factors and the Transcription Factors (genes/proteins) and the edges represent either splicing regulation or transcription regulation. The latter network demonstrated a high level regulation between proteins involved in the gene-expression pathway, involving both splicing and transcription regulation.

The talk will focus on three topics from my PhD thesis, which have applications also in other fields. The first concerns a clustering problem, in which the spatial data of objects are to be integrated with labels (e.g. features) of the objects. In the second the objects form the vertices of a graph and their labels are used to infer connections between communities of objects. The third is a new approach to statistical enrichment analysis, which takes into account degree of similarity between labels (instead of equality or non-equality). From a computational perspective the labels can be viewed (and will be presented in the talk) as colors, but the motivation for my resarch, as you all know, comes from attempts to improve the analysis of large scale data-sets of genes/gene-products.