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Processes 2015, 3(3), 607-618; doi:10.3390/pr3030607

Systems Biology of the Fluxome

Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD 21205 USA
Present address: National Institute on Aging, National Institutes of Health, BRC BG Rm 09B119, 251 Bayview Blvd., Baltimore, MD 21224, USA
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Author to whom correspondence should be addressed.
Academic Editor: Michael Henson
Received: 16 May 2015 / Accepted: 6 July 2015 / Published: 22 July 2015
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Abstract

The advent of high throughput -omics has made the accumulation of comprehensive data sets possible, consisting of changes in genes, transcripts, proteins and metabolites. Systems biology-inspired computational methods for translating metabolomics data into fluxomics provide a direct functional, dynamic readout of metabolic networks. When combined with appropriate experimental design, these methods deliver insightful knowledge about cellular function under diverse conditions. The use of computational models accounting for detailed kinetics and regulatory mechanisms allow us to unravel the control and regulatory properties of the fluxome under steady and time-dependent behaviors. This approach extends the analysis of complex systems from description to prediction, including control of complex dynamic behavior ranging from biological rhythms to catastrophic lethal arrhythmias. The powerful quantitative metabolomics-fluxomics approach will help our ability to engineer unicellular and multicellular organisms evolve from trial-and-error to a more predictable process, and from cells to organ and organisms. View Full-Text
Keywords: systems biology; metabolic disorders; diabetes; cancer; metabolomics; multi-scale modeling systems biology; metabolic disorders; diabetes; cancer; metabolomics; multi-scale modeling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Aon, M.A.; Cortassa, S. Systems Biology of the Fluxome. Processes 2015, 3, 607-618.

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