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Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

Overview of attention for article published in Molecular BioSystems, January 2015
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Mentioned by

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2 tweeters
facebook
1 Facebook page

Citations

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63 Dimensions

Readers on

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150 Mendeley
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Title
Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes
Published in
Molecular BioSystems, January 2015
DOI 10.1039/c5mb00158g
Pubmed ID
Authors

Mohamad Hafizi Abu Bakar, Mohamad Roji Sarmidi, Kian-Kai Cheng, Abid Ali Khan, Chua Lee Suan, Hasniza Zaman Huri, Harisun Yaakob

Abstract

Metabolomic studies on obesity and type 2 diabetes mellitus have led to a number of mechanistic insights into biomarker discovery and comprehension of disease progression at metabolic levels. This article reviews a series of metabolomic studies carried out in previous and recent years on obesity and type 2 diabetes, which have shown potential metabolic biomarkers for further evaluation of the diseases. Literature including journals and books from Web of Science, Pubmed and related databases reporting on the metabolomics in these particular disorders are reviewed. We herein discuss the potential of reported metabolic biomarkers for a novel understanding of disease processes. These biomarkers include fatty acids, TCA cycle intermediates, carbohydrates, amino acids, choline and bile acids. The biological activities and aetiological pathways of metabolites of interest in driving these intricate processes are explained. The data from various publications supported metabolomics as an effective strategy in the identification of novel biomarkers for obesity and type 2 diabetes. Accelerating interest in the perspective of metabolomics to complement other fields in systems biology towards the in-depth understanding of the molecular mechanisms underlying the diseases is also well appreciated. In conclusion, metabolomics can be used as one of the alternative approaches in biomarker discovery and the novel understanding of pathophysiological mechanisms in obesity and type 2 diabetes. It can be foreseen that there will be an increasing research interest to combine metabolomics with other omics platforms towards the establishment of detailed mechanistic evidence associated with the disease processes.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 150 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 1%
France 1 <1%
Netherlands 1 <1%
Malaysia 1 <1%
Spain 1 <1%
United States 1 <1%
Luxembourg 1 <1%
Unknown 142 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 34 23%
Student > Ph. D. Student 31 21%
Student > Master 24 16%
Student > Bachelor 13 9%
Student > Doctoral Student 12 8%
Other 26 17%
Unknown 10 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 36 24%
Agricultural and Biological Sciences 31 21%
Medicine and Dentistry 25 17%
Chemistry 12 8%
Nursing and Health Professions 6 4%
Other 22 15%
Unknown 18 12%

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 24 March 2016.
All research outputs
#10,186,038
of 15,983,397 outputs
Outputs from Molecular BioSystems
#719
of 1,368 outputs
Outputs of similar age
#127,806
of 232,082 outputs
Outputs of similar age from Molecular BioSystems
#19
of 56 outputs
Altmetric has tracked 15,983,397 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,368 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 37th percentile – i.e., 37% 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 232,082 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.