↓ Skip to main content

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

Overview of attention for article published in Frontiers in Aging Neuroscience, February 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
3 X users

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
84 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network
Published in
Frontiers in Aging Neuroscience, February 2017
DOI 10.3389/fnagi.2017.00023
Pubmed ID
Authors

Cynthia A. Martín-Jiménez, Diego Salazar-Barreto, George E. Barreto, Janneth González

Abstract

Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework to elucidate how astrocytes modulate human brain metabolic states during normal conditions and in neurodegenerative diseases. We performed a Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network with the purpose of elucidating a significant portion of the metabolic map of the astrocyte. This is the first global high-quality, manually curated metabolic reconstruction network of a human astrocyte. It includes 5,007 metabolites and 5,659 reactions distributed among 8 cell compartments, (extracellular, cytoplasm, mitochondria, endoplasmic reticle, Golgi apparatus, lysosome, peroxisome and nucleus). Using the reconstructed network, the metabolic capabilities of human astrocytes were calculated and compared both in normal and ischemic conditions. We identified reactions activated in these two states, which can be useful for understanding the astrocytic pathways that are affected during brain disease. Additionally, we also showed that the obtained flux distributions in the model, are in accordance with literature-based findings. Up to date, this is the most complete representation of the human astrocyte in terms of inclusion of genes, proteins, reactions and metabolic pathways, being a useful guide for in-silico analysis of several metabolic behaviors of the astrocyte during normal and pathologic states.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Singapore 1 1%
Unknown 82 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 18%
Student > Master 11 13%
Student > Bachelor 10 12%
Researcher 9 11%
Student > Doctoral Student 6 7%
Other 13 15%
Unknown 20 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 19 23%
Agricultural and Biological Sciences 12 14%
Neuroscience 8 10%
Computer Science 4 5%
Engineering 4 5%
Other 12 14%
Unknown 25 30%
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 16 February 2017.
All research outputs
#15,443,875
of 22,953,506 outputs
Outputs from Frontiers in Aging Neuroscience
#3,617
of 4,829 outputs
Outputs of similar age
#260,202
of 426,820 outputs
Outputs of similar age from Frontiers in Aging Neuroscience
#82
of 100 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,829 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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 426,820 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.