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Analysis of molecular networks and targets mining of Chinese herbal medicines on anti-aging

Overview of attention for article published in BMC Complementary Medicine and Therapies, December 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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1 news outlet
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10 X users
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2 Facebook pages
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2 Google+ users

Citations

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5 Dimensions

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23 Mendeley
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Title
Analysis of molecular networks and targets mining of Chinese herbal medicines on anti-aging
Published in
BMC Complementary Medicine and Therapies, December 2016
DOI 10.1186/s12906-016-1513-2
Pubmed ID
Authors

Qi-yu Jiang, Mei-si Zheng, Xiao-jing Yang, Xiao-sheng Sun

Abstract

Many kidney-tonifying Chinese herbal medicines exert effects on anti-aging by comprehensive interactions of multiple targets. However, the interactions of multi-targets targeted by effective ingredients of kidney-tonifying Chinese herbal medicines are unknown. In this study, to explore the systems pharmacology mechanisms of kidney-tonifying Chinese medicines on anti-aging, we establish the molecular networks with the interactions of multi-targets, analyze bio-functions and pathways with IPA, and calculated the mutual interaction pairs of targets (target pairs) with data mining, respectively. Kidney-tonifying Chinese medicines with anti-aging effects were screened from the Chinese Pharmacopoeia and the literatures. Target proteins of these herbal medicines were obtained from bioinformatics databases. Comparisons of molecular networks, bio-functions and pathways given by Ingenuity Pathway Analysis system showed the similarities and the differences between kidney Yin-tonifying herbal medicines and kidney Yang-tonifying herbal medicines. Target pairs with high correlation related to anti-aging were also discovered by data mining algorithm. And regulatory networks of targets were built based on the target pairs. Twenty-eight kidney-tonifying herbal medicines with anti-aging effects and 717 related target proteins were collected. The main bio-functions that all targets enriched in were "Cell Death and Survival", "Free Radical Scavenging" and "Cellular Movement", etc. The results of comparison analysis showed that kidney Yin-tonifying herbal medicines focused more on "Cancer related signaling", "Apoptosis related signaling" and "Cardiovascular related signaling". And kidney Yang-tonifying herbal medicines focused more on "Cellular stress and injury related signaling" and "Cellular growth, proliferation and development related signaling". Moreover, the results of regulatory network showed that the anti-aging related target pairs with high correlated degrees of Kidney Yin-tonifying herbal medicines included TNF-PTGS2, TNF-CASP3, PTGS2-CASP3, CASP3-NOS2 and TNF-NOS2, and that of kidney Yang-tonifying herbal medicines included REAL-TNF, REAL-NFKBIA, REAL-JUN, PTGS2-SOD1 and TNF-IL6. In this study, we achieved some important targets, target pairs and regulatory networks with bioinformatics and data mining, to discuss the systems pharmacology mechanisms of kidney-tonifying herbal medicines acting on anti-aging. Mutual target pairs related to anti-aging found in this study included TNF-PTGS2, TNF-CASP3, PTGS2-CASP3, CASP3-NOS2, TNF-NOS2, REAL-TNF, REAL-NFKBIA, REAL-JUN, PTGS2-SOD1 and TNF-IL6. Target pairs and regulatory networks of targets could reflect more potential interactions between targets and comprehensive effects on anti-aging. Compared with the existing researches, it was found that the kidney-tonifying herbal medicines may exert anti-aging effects in multiple pathways in this study.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 22%
Student > Ph. D. Student 3 13%
Researcher 2 9%
Student > Postgraduate 2 9%
Lecturer > Senior Lecturer 1 4%
Other 3 13%
Unknown 7 30%
Readers by discipline Count As %
Medicine and Dentistry 6 26%
Nursing and Health Professions 3 13%
Biochemistry, Genetics and Molecular Biology 2 9%
Psychology 2 9%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Other 2 9%
Unknown 7 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 15 November 2017.
All research outputs
#1,845,520
of 22,925,760 outputs
Outputs from BMC Complementary Medicine and Therapies
#319
of 3,639 outputs
Outputs of similar age
#40,635
of 421,162 outputs
Outputs of similar age from BMC Complementary Medicine and Therapies
#6
of 73 outputs
Altmetric has tracked 22,925,760 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,639 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one has done particularly well, scoring higher than 91% of its peers.
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 421,162 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.