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Exploring Biotic Interactions Within Protist Cell Populations Using Network Methods

Overview of attention for article published in Journal of Eukaryotic Microbiology, May 2014
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Article details
Title
Exploring Biotic Interactions Within Protist Cell Populations Using Network Methods
Published in
Journal of Eukaryotic Microbiology, May 2014
DOI 10.1111/jeu.12113
Pubmed ID
Authors
Abstract

The study of diseased human cells and of cells isolated from the natural environment will likely be revolutionized by single cell genomics (SCG). Here, we used protein similarity networks to explore within- and between-cell DNA differences from SCG data derived from six individual rhizarian cells related to Paulinella ovalis and proteins from the complete genome of another rhizarian, Bigelowiella natans. We identified shared and distinct DNA components within our SCG data and between P. ovalis and B. natans. We show that network properties such as assortativity and degree effectively discriminate genome features between SCG assemblies and that SCG data follow the power law with a small number of protein families dominating networks.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
France 1 14%
Unknown 6 86%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 3 43%
Other 1 14%
Student > Doctoral Student 1 14%
Professor 1 14%
Student > Ph. D. Student 1 14%
Other 0 0%
Readers by discipline
Readers by discipline Count As %
Agricultural and Biological Sciences 3 43%
Biochemistry, Genetics and Molecular Biology 2 29%
Veterinary Science and Veterinary Medicine 1 14%
Neuroscience 1 14%
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 19 March 2014.
All research outputs
#22,003,549
of 24,549,201 outputs
Outputs from Journal of Eukaryotic Microbiology
#926
of 1,022 outputs
Outputs of similar age
#200,597
of 232,118 outputs
Outputs of similar age from Journal of Eukaryotic Microbiology
#6
of 8 outputs
Altmetric has tracked 24,549,201 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,022 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% 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 232,118 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.