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Systems approaches to computational modeling of the oral microbiome

Overview of attention for article published in Frontiers in Physiology, January 2013
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2 X users
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1 Facebook page

Citations

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11 Dimensions

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78 Mendeley
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1 CiteULike
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Title
Systems approaches to computational modeling of the oral microbiome
Published in
Frontiers in Physiology, January 2013
DOI 10.3389/fphys.2013.00172
Pubmed ID
Authors

Dimiter V Dimitrov, Julia Hoeng

Abstract

Current microbiome research has generated tremendous amounts of data providing snapshots of molecular activity in a variety of organisms, environments, and cell types. However, turning this knowledge into whole system level of understanding on pathways and processes has proven to be a challenging task. In this review we highlight the applicability of bioinformatics and visualization techniques to large collections of data in order to better understand the information that contains related diet-oral microbiome-host mucosal transcriptome interactions. In particular, we focus on systems biology of Porphyromonas gingivalis in the context of high throughput computational methods tightly integrated with translational systems medicine. Those approaches have applications for both basic research, where we can direct specific laboratory experiments in model organisms and cell cultures, and human disease, where we can validate new mechanisms and biomarkers for prevention and treatment of chronic disorders.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Germany 1 1%
Switzerland 1 1%
Unknown 74 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 29%
Researcher 12 15%
Student > Master 9 12%
Student > Postgraduate 8 10%
Other 4 5%
Other 10 13%
Unknown 12 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 36%
Medicine and Dentistry 12 15%
Biochemistry, Genetics and Molecular Biology 5 6%
Chemistry 3 4%
Nursing and Health Professions 2 3%
Other 11 14%
Unknown 17 22%
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 04 November 2017.
All research outputs
#15,274,055
of 22,713,403 outputs
Outputs from Frontiers in Physiology
#6,610
of 13,524 outputs
Outputs of similar age
#181,521
of 280,747 outputs
Outputs of similar age from Frontiers in Physiology
#188
of 398 outputs
Altmetric has tracked 22,713,403 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 13,524 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one is in the 47th percentile – i.e., 47% 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 280,747 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 398 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 50% of its contemporaries.