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Macro-level Modeling of the Response of C. elegans Reproduction to Chronic Heat Stress

Overview of attention for article published in PLoS Computational Biology, January 2012
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Title
Macro-level Modeling of the Response of C. elegans Reproduction to Chronic Heat Stress
Published in
PLoS Computational Biology, January 2012
DOI 10.1371/journal.pcbi.1002338
Pubmed ID
Authors

Patrick D. McMullen, Erin Z. Aprison, Peter B. Winter, Luis A. N. Amaral, Richard I. Morimoto, Ilya Ruvinsky

Abstract

A major goal of systems biology is to understand how organism-level behavior arises from a myriad of molecular interactions. Often this involves complex sets of rules describing interactions among a large number of components. As an alternative, we have developed a simple, macro-level model to describe how chronic temperature stress affects reproduction in C. elegans. Our approach uses fundamental engineering principles, together with a limited set of experimentally derived facts, and provides quantitatively accurate predictions of performance under a range of physiologically relevant conditions. We generated detailed time-resolved experimental data to evaluate the ability of our model to describe the dynamics of C. elegans reproduction. We find considerable heterogeneity in responses of individual animals to heat stress, which can be understood as modulation of a few processes and may represent a strategy for coping with the ever-changing environment. Our experimental results and model provide quantitative insight into the breakdown of a robust biological system under stress and suggest, surprisingly, that the behavior of complex biological systems may be determined by a small number of key components.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 2%
United Kingdom 1 1%
Portugal 1 1%
United States 1 1%
Poland 1 1%
Unknown 75 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 30%
Researcher 17 21%
Student > Bachelor 9 11%
Student > Master 9 11%
Professor 6 7%
Other 9 11%
Unknown 7 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 44%
Biochemistry, Genetics and Molecular Biology 12 15%
Engineering 7 9%
Physics and Astronomy 5 6%
Environmental Science 3 4%
Other 10 12%
Unknown 8 10%