Expression profiling of whole genomes, and modern high-throughput proteomics, has created a revolution in the study of disease states. Approaches for gene expression analysis (time series analysis and clustering) have been applied to functional genomics related to cancer research, and have yielded major successes in the pursuit of gene expression signatures. However, these analysis methods are primarily designed to identify correlative or causal relationships between entities, but do not consider the data in the proper biological context of a “biological pathway” model. Pathway models form a cornerstone of systems biology. They provide a framework for (1) systematic interrogation of biochemical interactions, (2) management of the collective knowledge pertaining to cellular components, and (3) discovery of emergent properties of different pathway configurations
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