The integrated informatics architecture proposed here will facilitate the construction of gene regulatory and other biological pathway models from networks of molecular and phenotypic associations. Current commercial or academic solutions are mostly limited to basic analysis of array data to determine differential expression and do not practically address the advanced analysis of array data to uncover sets of regulatory associations between genes. Moreover, no commercial solutions exist to assist scientists in the critically important task of taking the results of these advanced analyses and assembling testable models from them. The work proposed here will create a next generation informatics architecture that overcomes these deficiencies by providing (1) advanced analytical methods to identify from either Affymetrix or De Novo spotted RNA array data networks of regulatory associations between genes and (2) methods to assist in the interpretation of function genomic results by providing methods to build gene-phenotype association models about which, how and where molecules associate with one another and what are the molecular and phenotypic effects of the association. The components of the architecture will be able with freely exchange information with biological databases, literature mining, analysis and visualization applications to allow better interpretation of the resulting analyses and models.
Benefits: The contribution of this technology to advancing research capabilities should be realized in both commercial and academic/non-for-profit settings alike. With regard to commercial organizations, it will allow biopharmaceutical companies to: 1) Prioritize new drug targets by understanding the significance of their biochemical pathways; 2) Find alternative targets in pathways of non-druggable targets; 3) Identify novel combinations of drug targets and develop combination drug therapies; 4) Prioritize lead compounds in the context of the biochemical circuitry controlling the disease; 5) Predict the toxicological effects of lead compounds. To the extent that this technology has a measurable impact on improving the productivity of pharmaceutical R&D organizations, which is currently of tremendous concern to the industry, the wider societal and economic benefits will be considerable.
Keywords: expression analysis, pathways, gene regulatory networks, microarrays, data integration, model building, decision support
