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AraGEM, a Genome-Scale Reconstruction of the Primary Metabolic Network in Arabidopsis

Overview of attention for article published in Plant Physiology, December 2009
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  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Citations

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297 Dimensions

Readers on

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413 Mendeley
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3 CiteULike
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Title
AraGEM, a Genome-Scale Reconstruction of the Primary Metabolic Network in Arabidopsis
Published in
Plant Physiology, December 2009
DOI 10.1104/pp.109.148817
Pubmed ID
Authors

Cristiana Gomes de Oliveira Dal'Molin, Lake-Ee Quek, Robin William Palfreyman, Stevens Michael Brumbley, Lars Keld Nielsen

Abstract

Genome-scale metabolic network models have been successfully used to describe metabolism in a variety of microbial organisms as well as specific mammalian cell types and organelles. This systems-based framework enables the exploration of global phenotypic effects of gene knockouts, gene insertion, and up-regulation of gene expression. We have developed a genome-scale metabolic network model (AraGEM) covering primary metabolism for a compartmentalized plant cell based on the Arabidopsis (Arabidopsis thaliana) genome. AraGEM is a comprehensive literature-based, genome-scale metabolic reconstruction that accounts for the functions of 1,419 unique open reading frames, 1,748 metabolites, 5,253 gene-enzyme reaction-association entries, and 1,567 unique reactions compartmentalized into the cytoplasm, mitochondrion, plastid, peroxisome, and vacuole. The curation process identified 75 essential reactions with respective enzyme associations not assigned to any particular gene in the Kyoto Encyclopedia of Genes and Genomes or AraCyc. With the addition of these reactions, AraGEM describes a functional primary metabolism of Arabidopsis. The reconstructed network was transformed into an in silico metabolic flux model of plant metabolism and validated through the simulation of plant metabolic functions inferred from the literature. Using efficient resource utilization as the optimality criterion, AraGEM predicted the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. AraGEM is a viable framework for in silico functional analysis and can be used to derive new, nontrivial hypotheses for exploring plant metabolism.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 413 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 9 2%
United States 7 2%
France 5 1%
Netherlands 2 <1%
Denmark 2 <1%
Iran, Islamic Republic of 2 <1%
United Kingdom 2 <1%
Portugal 1 <1%
Ireland 1 <1%
Other 14 3%
Unknown 368 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 105 25%
Researcher 83 20%
Student > Master 60 15%
Student > Bachelor 25 6%
Student > Doctoral Student 24 6%
Other 63 15%
Unknown 53 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 218 53%
Biochemistry, Genetics and Molecular Biology 58 14%
Engineering 24 6%
Computer Science 22 5%
Chemical Engineering 8 2%
Other 17 4%
Unknown 66 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 17 April 2018.
All research outputs
#7,356,550
of 25,374,917 outputs
Outputs from Plant Physiology
#5,399
of 12,429 outputs
Outputs of similar age
#43,332
of 172,529 outputs
Outputs of similar age from Plant Physiology
#16
of 51 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 12,429 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 172,529 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.