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OCDD: an obesity and co-morbid disease database

Overview of attention for article published in BioData Mining, November 2017
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Title
OCDD: an obesity and co-morbid disease database
Published in
BioData Mining, November 2017
DOI 10.1186/s13040-017-0153-5
Pubmed ID
Authors

Indrani Ray, Anindya Bhattacharya, Rajat K. De

Abstract

Obesity is a medical condition that is known for increased body mass index (BMI). It is also associated with chronic low level inflammation. Obesity disrupts the immune-metabolic homeostasis by changing the secretion of adipocytes. This affects the end-organs, and gives rise to several diseases including type 2 diabetes, asthma, non-alcoholic fatty liver diseases and cancers. These diseases are known as co-morbid diseases. Several studies have explored the underlying molecular mechanisms of developing obesity associated comorbid diseases. To understand the development and progression of diseases associated with obesity, we need a detailed scenario of gene interactions and the distribution of the responsible genes in human system. Obesity and Co-morbid Disease Database (OCDD) is designed for relating obesity and its co-morbid diseases using literature mining, and computational and systems biology approaches. OCDD is aimed to investigate the genes associated with comorbidity. Several existing databases have been used to extract molecular interactions and functional annotations of each gene. The degree of co-morbid associations has been measured and made available to the users. The database is available at http://www.isical.ac.in/~systemsbiology/OCDD/home.php. The main objective of the database is to derive the relations among the genes that are involved in both obesity and its co-morbid diseases. Functional annotation of common genes, gene interaction networks and key driver analyses have made the database a valuable and comprehensive resource for investigating the causal links between obesity and co-morbid diseases.

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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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 21%
Student > Bachelor 5 15%
Student > Master 4 12%
Researcher 2 6%
Other 2 6%
Other 4 12%
Unknown 9 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 18%
Medicine and Dentistry 6 18%
Agricultural and Biological Sciences 4 12%
Computer Science 4 12%
Economics, Econometrics and Finance 1 3%
Other 3 9%
Unknown 9 27%
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 05 December 2017.
All research outputs
#15,484,498
of 23,009,818 outputs
Outputs from BioData Mining
#226
of 309 outputs
Outputs of similar age
#265,058
of 437,742 outputs
Outputs of similar age from BioData Mining
#6
of 8 outputs
Altmetric has tracked 23,009,818 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 309 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 19th percentile – i.e., 19% 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 437,742 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.