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Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses

Overview of attention for article published in PLoS Computational Biology, June 2010
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Title
Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses
Published in
PLoS Computational Biology, June 2010
DOI 10.1371/journal.pcbi.1000820
Pubmed ID
Authors

Andres Kriete, William J. Bosl, Glenn Booker

Abstract

Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-kappaB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype.

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The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 5%
United Kingdom 3 2%
Brazil 2 2%
Germany 2 2%
Mexico 1 <1%
Unknown 109 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 41 33%
Student > Ph. D. Student 25 20%
Professor > Associate Professor 14 11%
Student > Bachelor 9 7%
Student > Master 8 7%
Other 17 14%
Unknown 9 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 43%
Biochemistry, Genetics and Molecular Biology 18 15%
Medicine and Dentistry 15 12%
Mathematics 6 5%
Computer Science 4 3%
Other 13 11%
Unknown 14 11%