A computational framework to explore cellular response mechanisms from multi-omics datasets
Autor: | Alexander L. R. Lubbock, Leonard A. Harris, Jeremy L. Norris, James C. Pino, Carlos F. Lopez, Richard M. Caprioli, Danielle B. Gutierrez, John P. Wikswo, Melissa A. Farrow, Nicole D. Muszynski, Tina Tsui |
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Rok vydání: | 2020 |
Předmět: |
Bendamustine
Cell cycle checkpoint Computer science Data management Human immunodeficiency virus (HIV) Computational biology medicine.disease_cause computer.software_genre Transcriptome 03 medical and health sciences medicine 030304 developmental biology 0303 health sciences business.industry 030302 biochemistry & molecular biology 3. Good health Visualization Software framework Mechanism of action Apoptosis Proteome Multi omics medicine.symptom business computer medicine.drug |
Popis: | 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 MAGINE, a software framework to explore complex time-course multi-omics datasets and build mechanistic hypotheses of dynamic cellular response. MAGINE combines data management, enrichment, and network analysis and visualization within an interactive, Jupyter notebook-based environment to enable human-in-the-loop inquiry of complex datasets. We demonstrate how measurements from HL-60 cellular response to bendamustine treatment can be used to build a mechanistic, multi-resolution description of cellular commitment to fate. We present a systems-level description of signal execution from cellular DNA-damage response, to cell cycle arrest, and eventual commitment to apoptosis, mediated by over 2000 biochemical species. We further show that MAGINE can reveal unexpected, non-canonical effects of bendamustine treatment, including disruption of cellular pathways relevant to HIV infection response. MAGINE is available fromhttps://github.com/lolab-vu/magine. |
Databáze: | OpenAIRE |
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