Cancer is a multifactorial disease the study and analysis of which naturally require the integration of disciplines, and the fusion of omics and clinical evidence. Each informative layer linked to such combined evidence involves a particular type of complexity, in part technology-driven and in part patient-dependent. Therefore, due to data dimensionality and heterogeneity the task for computational scientists is very challenging as it refers to data assimilation, mining and inference. Cancer-associated mechanisms refer to complex entities such as transcription factors and microRNA the influence of which is exerted over many distinct mRNA targets involved in key biological processes, both normal and altered ones. This work aims to propose an open source tool allowing inference on microRNA-target coordination involving cancer-induced dysregulation. By introducing Mirware, a novel warehouse of genes is provided to specifically and uniquely build a cancer repository based on publicly available data from Array Express, and populated by importing from Tarbase and Mirbase all the known associations between microRNAs and target genes. Coordination can be assessed by merging profiling from gene co-expression measurements and clinical evidence integrated to them. Data have been organized by tissue, such that microRNA-mRNA association matrices can be built based on both experimental and predicted data, thus promising to offer a contribution to build a knowledge base clarifying cancer regulation mechanisms.
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