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Network Identification of Hormonal Regulation

Overview of attention for article published in PLOS ONE, May 2014
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1 X user

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Title
Network Identification of Hormonal Regulation
Published in
PLOS ONE, May 2014
DOI 10.1371/journal.pone.0096284
Pubmed ID
Authors

Daniel J. Vis, Johan A. Westerhuis, Huub C. J. Hoefsloot, Ferdinand Roelfsema, Jan van der Greef, Margriet M. W. B. Hendriks, Age K. Smilde

Abstract

Relations among hormone serum concentrations are complex and depend on various factors, including gender, age, body mass index, diurnal rhythms and secretion stochastics. Therefore, endocrine deviations from healthy homeostasis are not easily detected or understood. A generic method is presented for detecting regulatory relations between hormones. This is demonstrated with a cohort of obese women, who underwent blood sampling at 10 minute intervals for 24-hours. The cohort was treated with bromocriptine in an attempt to clarify how hormone relations change by treatment. The detected regulatory relations are summarized in a network graph and treatment-induced changes in the relations are determined. The proposed method identifies many relations, including well-known ones. Ultimately, the method provides ways to improve the description and understanding of normal hormonal relations and deviations caused by disease or treatment.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 4%
United States 1 4%
South Africa 1 4%
Unknown 20 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 35%
Other 3 13%
Student > Bachelor 3 13%
Student > Master 2 9%
Researcher 2 9%
Other 2 9%
Unknown 3 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 26%
Medicine and Dentistry 6 26%
Nursing and Health Professions 1 4%
Arts and Humanities 1 4%
Psychology 1 4%
Other 3 13%
Unknown 5 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 23 May 2014.
All research outputs
#18,372,841
of 22,756,196 outputs
Outputs from PLOS ONE
#154,407
of 194,180 outputs
Outputs of similar age
#162,985
of 226,264 outputs
Outputs of similar age from PLOS ONE
#3,458
of 4,633 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,180 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 10th percentile – i.e., 10% 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 226,264 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4,633 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.