2020
DOI: 10.1101/2020.03.02.974121
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A computational framework to explore cellular response mechanisms from multi-omics datasets

Abstract: 1 † These authors contributed equally to this work.Recent technological advances have made it feasible to collect multi-condition transcriptome and proteome time-courses of cellular response to perturbation. The increasing size and complexity of these datasets impedes mechanism of action discovery due to challenges in data management, analysis, visualization, and interpretation. Here, we introduce MAG-INE, a software framework to explore complex time-course multi-omics datasets and build mechanistic hypotheses… Show more

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“…These proteins were determined using external pathway mapping tools and entered into Reactome, 105 and the resulting list of proteins associated with metabolism were input into SIMONE 106 as seed proteins. This tool constructs networks using the MAGINE framework, 107 which derives protein connection information from multiple databases (Figure S2). By uncovering how these proteins are connected, pathways can be predicted from spatiotemporal proteomics data.…”
Section: ■ Results and Discussionmentioning
confidence: 99%
“…These proteins were determined using external pathway mapping tools and entered into Reactome, 105 and the resulting list of proteins associated with metabolism were input into SIMONE 106 as seed proteins. This tool constructs networks using the MAGINE framework, 107 which derives protein connection information from multiple databases (Figure S2). By uncovering how these proteins are connected, pathways can be predicted from spatiotemporal proteomics data.…”
Section: ■ Results and Discussionmentioning
confidence: 99%