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LENS: web-based lens for enrichment and network studies of human proteins

Overview of attention for article published in BMC Medical Genomics, December 2015
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
LENS: web-based lens for enrichment and network studies of human proteins
Published in
BMC Medical Genomics, December 2015
DOI 10.1186/1755-8794-8-s4-s2
Pubmed ID
Authors

Adam Handen, Madhavi K Ganapathiraju

Abstract

Network analysis is a common approach for the study of genetic view of diseases and biological pathways. Typically, when a set of genes are identified to be of interest in relation to a disease, say through a genome wide association study (GWAS) or a different gene expression study, these genes are typically analyzed in the context of their protein-protein interaction (PPI) networks. Further analysis is carried out to compute the enrichment of known pathways and disease-associations in the network. Having tools for such analysis at the fingertips of biologists without the requirement for computer programming or curation of data would accelerate the characterization of genes of interest. Currently available tools do not integrate network and enrichment analysis and their visualizations, and most of them present results in formats not most conducive to human cognition. We developed the tool Lens for Enrichment and Network Studies of human proteins (LENS) that performs network and pathway and diseases enrichment analyses on genes of interest to users. The tool creates a visualization of the network, provides easy to read statistics on network connectivity, and displays Venn diagrams with statistical significance values of the network's association with drugs, diseases, pathways, and GWASs. We used the tool to analyze gene sets related to craniofacial development, autism, and schizophrenia. LENS is a web-based tool that does not require and download or plugins to use. The tool is free and does not require login for use, and is available at http://severus.dbmi.pitt.edu/LENS.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 23%
Student > Ph. D. Student 5 14%
Student > Bachelor 4 11%
Student > Doctoral Student 2 6%
Other 2 6%
Other 5 14%
Unknown 9 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 17%
Agricultural and Biological Sciences 5 14%
Medicine and Dentistry 4 11%
Psychology 3 9%
Computer Science 2 6%
Other 6 17%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 20 November 2017.
All research outputs
#13,377,140
of 22,835,198 outputs
Outputs from BMC Medical Genomics
#495
of 1,223 outputs
Outputs of similar age
#185,932
of 389,036 outputs
Outputs of similar age from BMC Medical Genomics
#18
of 34 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,223 research outputs from this source. They receive a mean Attention Score of 4.7. 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 389,036 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.