black microarray DiGE ECCB Satellite Meeting on
Probabilistic Modelling in Computational Biology
22 Sept 2008 Cagliari, Sardinia

Probabilistic Methods for
Dynamic System Models and Data Integration in Computational Biology

Affiliated with ECCB 2008

The extraction of an improved biological understanding from genome-scale quantitative measurements, like microarray data, has recently been a very active area of bioinformatics research. In particular, models based on these data are used in the investigation of complex interactions with many players, many of which cannot easily be studied in traditional ways because experimental interference is either lethal or shows no obvious phenotypical effect due to redundancies. Frequent tasks in such research work include the identification of common molecular mechanisms and the detection of causal effects, in particular, the mapping of regulatory pathways.

The required inference of the often highly complex models of biological processes involves large numbers of interacting variables that have to be chosen from a pool of tens of thousands of candidates. The high dimensionality of the problem is starkly contrasted by the very small numbers of samples that can be obtained by direct assays. This makes an efficient use of contextual information critical.

The difficulty of an integrated analysis is compounded by the heterogeneous nature of contextual knowledge available. Data sources vary considerably with respect to comprehensiveness, error rates, and suitability for direct computational exploitation. Besides data from microarrays for gene expression profiling, some typical representatives of different data classes are: abstracted relationships between biological entities (e.g., Gene Ontology); curated pathway descriptions (e.g., KEGG or EcoCyc), curated functional annotation (e.g., UniProt/SWISS-PROT); results from de novo sequence analysis (e.g., phosphorylation site predictions); data from protein-protein interaction experiments (e.g., Y2H screens); and experimentally detected protein-DNA binding sites (e.g., ChIP-chip results).

Efficiently taking advantage of these data for inference or dynamic modelling raises many technical, conceptual, and analytical challenges. In this ECCB Satellite Meeting, we will explore these issues with an emphasis on probabilistic methods. This meeting succeeds the PMCB 2007 workshop affiliated with ISMB/ECCB'07, which attracted over 50 participants. This year's meeting will be organized in two themed sessions.

  Vienna Science and Technology Fund (WWTF)     Boku Bioinformatics