Big: A large-scale data integration tool for renal physiology

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Abstract

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: “How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?” This is the type of problem that has motivated the “Big-Data” revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/.

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Zhao, Y., Yang, C. R., Raghuram, V., Parulekar, J., & Knepper, M. A. (2016). Big: A large-scale data integration tool for renal physiology. American Journal of Physiology - Renal Physiology, 311(4), F787–F792. https://doi.org/10.1152/ajprenal.00249.2016

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