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Unexpected links reflect the noise in networks

Overview of attention for article published in Biology Direct, October 2016
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Mentioned by

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4 tweeters

Citations

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22 Dimensions

Readers on

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27 Mendeley
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Title
Unexpected links reflect the noise in networks
Published in
Biology Direct, October 2016
DOI 10.1186/s13062-016-0155-0
Pubmed ID
Authors

Anatoly Yambartsev, Michael A. Perlin, Yevgeniy Kovchegov, Natalia Shulzhenko, Karina L. Mine, Xiaoxi Dong, Andrey Morgun

Abstract

Gene covariation networks are commonly used to study biological processes. The inference of gene covariation networks from observational data can be challenging, especially considering the large number of players involved and the small number of biological replicates available for analysis. We propose a new statistical method for estimating the number of erroneous edges in reconstructed networks that strongly enhances commonly used inference approaches. This method is based on a special relationship between sign of correlation (positive/negative) and directionality (up/down) of gene regulation, and allows for the identification and removal of approximately half of all erroneous edges. Using the mathematical model of Bayesian networks and positive correlation inequalities we establish a mathematical foundation for our method. Analyzing existing biological datasets, we find a strong correlation between the results of our method and false discovery rate (FDR). Furthermore, simulation analysis demonstrates that our method provides a more accurate estimate of network error than FDR. Thus, our study provides a new robust approach for improving reconstruction of covariation networks. This article was reviewed by Eugene Koonin, Sergei Maslov, Daniel Yasumasa Takahashi.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 7%
China 1 4%
France 1 4%
Taiwan 1 4%
Unknown 22 81%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 19%
Researcher 5 19%
Professor 3 11%
Student > Doctoral Student 2 7%
Unspecified 2 7%
Other 5 19%
Unknown 5 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 22%
Biochemistry, Genetics and Molecular Biology 5 19%
Computer Science 3 11%
Arts and Humanities 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Other 4 15%
Unknown 7 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 14 February 2018.
All research outputs
#9,941,316
of 16,185,167 outputs
Outputs from Biology Direct
#326
of 589 outputs
Outputs of similar age
#101,799
of 190,022 outputs
Outputs of similar age from Biology Direct
#15
of 18 outputs
Altmetric has tracked 16,185,167 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 589 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 42nd percentile – i.e., 42% 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 190,022 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.