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Functional Modules, Structural Topology, and Optimal Activity in Metabolic Networks

Overview of attention for article published in PLoS Computational Biology, October 2012
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Title
Functional Modules, Structural Topology, and Optimal Activity in Metabolic Networks
Published in
PLoS Computational Biology, October 2012
DOI 10.1371/journal.pcbi.1002720
Pubmed ID
Authors

Osbaldo Resendis-Antonio, Magdalena Hernández, Yolanda Mora, Sergio Encarnación

Abstract

Modular organization in biological networks has been suggested as a natural mechanism by which a cell coordinates its metabolic strategies for evolving and responding to environmental perturbations. To understand how this occurs, there is a need for developing computational schemes that contribute to integration of genomic-scale information and assist investigators in formulating biological hypotheses in a quantitative and systematic fashion. In this work, we combined metabolome data and constraint-based modeling to elucidate the relationships among structural modules, functional organization, and the optimal metabolic phenotype of Rhizobium etli, a bacterium that fixes nitrogen in symbiosis with Phaseolus vulgaris. To experimentally characterize the metabolic phenotype of this microorganism, we obtained the metabolic profile of 220 metabolites at two physiological stages: under free-living conditions, and during nitrogen fixation with P. vulgaris. By integrating these data into a constraint-based model, we built a refined computational platform with the capability to survey the metabolic activity underlying nitrogen fixation in R. etli. Topological analysis of the metabolic reconstruction led us to identify modular structures with functional activities. Consistent with modular activity in metabolism, we found that most of the metabolites experimentally detected in each module simultaneously increased their relative abundances during nitrogen fixation. In this work, we explore the relationships among topology, biological function, and optimal activity in the metabolism of R. etli through an integrative analysis based on modeling and metabolome data. Our findings suggest that the metabolic activity during nitrogen fixation is supported by interacting structural modules that correlate with three functional classifications: nucleic acids, peptides, and lipids. More fundamentally, we supply evidence that such modular organization during functional nitrogen fixation is a robust property under different environmental conditions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 2%
Germany 2 2%
United States 2 2%
Netherlands 1 <1%
Australia 1 <1%
Colombia 1 <1%
Singapore 1 <1%
Iran, Islamic Republic of 1 <1%
Mexico 1 <1%
Other 5 4%
Unknown 98 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 29%
Student > Ph. D. Student 32 28%
Student > Master 14 12%
Professor > Associate Professor 6 5%
Student > Bachelor 5 4%
Other 16 14%
Unknown 9 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 53 46%
Biochemistry, Genetics and Molecular Biology 13 11%
Computer Science 11 10%
Medicine and Dentistry 7 6%
Engineering 7 6%
Other 14 12%
Unknown 10 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 October 2012.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from PLoS Computational Biology
#7,480
of 8,960 outputs
Outputs of similar age
#126,009
of 191,748 outputs
Outputs of similar age from PLoS Computational Biology
#77
of 107 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.