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Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease

Overview of attention for article published in Frontiers in Cardiovascular Medicine, February 2017
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2 X users

Citations

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26 Dimensions

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76 Mendeley
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Title
Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease
Published in
Frontiers in Cardiovascular Medicine, February 2017
DOI 10.3389/fcvm.2017.00008
Pubmed ID
Authors

Douglas Arneson, Le Shu, Brandon Tsai, Rio Barrere-Cain, Christine Sun, Xia Yang

Abstract

Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field.

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

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 21 28%
Student > Ph. D. Student 13 17%
Student > Bachelor 11 14%
Student > Master 7 9%
Student > Doctoral Student 4 5%
Other 10 13%
Unknown 10 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 22 29%
Agricultural and Biological Sciences 12 16%
Medicine and Dentistry 11 14%
Engineering 6 8%
Computer Science 3 4%
Other 9 12%
Unknown 13 17%
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 27 February 2017.
All research outputs
#15,448,169
of 22,957,478 outputs
Outputs from Frontiers in Cardiovascular Medicine
#2,588
of 6,860 outputs
Outputs of similar age
#198,269
of 312,054 outputs
Outputs of similar age from Frontiers in Cardiovascular Medicine
#9
of 20 outputs
Altmetric has tracked 22,957,478 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 6,860 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 59% 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 312,054 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.