technical report Towards the integration of computational systems biology and high-throughput data: a way to support differential analysis of microarray gene expression data


The paradigmatic shift occurred in biology that led ¯rst to high-throughput experimental techniques and later to computational sys- tems biology must be applied also to the analysis paradigm of the relation between local models and data to obtain an e®ective prediction frame- work. In this work we show that the new relation between systems biol- ogy models and high-throughput data permits new integrations on the systemic scale like the use of in silico predictions to support the mining of gene expression datasets. We introduce a unifying notational frame- work in which we propose two applications concerning the use of system level models to support the di®erential analysis of microarray expression data. The approach is tested with a speci¯c microarray experiment on the phosphate system in Saccharomyces cerevisiae and a computational model of the PHO pathway that supports the systems biology concepts.

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N. Segata,  E. Blanzieri,  C. Priami