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Integrative analysis of gene expression and methylation data for breast cancer cell lines

Overview of attention for article published in BioData Mining, June 2018
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1 tweeter

Citations

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19 Mendeley
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Title
Integrative analysis of gene expression and methylation data for breast cancer cell lines
Published in
BioData Mining, June 2018
DOI 10.1186/s13040-018-0174-8
Pubmed ID
Authors

Catherine Li, Juyon Lee, Jessica Ding, Shuying Sun

Abstract

The deadly costs of cancer and necessity for an accurate method of early cancer detection have demanded the identification of genetic and epigenetic factors associated with cancer. DNA methylation, an epigenetic event, plays an important role in cancer susceptibility. In this paper, we use DNA methylation and gene expression data integration and pathway analysis to further explore and understand the complex relationship between methylation and gene expression. Through linear modeling and analysis of variance, we obtain genes that show a significant correlation between methylation and gene expression. We then examine the functions and relationships of these genes using bioinformatic tools and databases. In particular, using ConsensusPathDB, we analyze the networks of statistically significant genes to identify hub genes, genes with a large number of links to other genes. We identify eight major hub genes, all in strong association with cancer susceptibility. Through further analysis of the function, gene expression level, and methylation level of these hub genes, we conclude that they are novel potential biomarkers for breast cancer. Our findings have various implications for cancer screening, early detection methods, and potential novel treatments for cancer. Researchers can also use our results to develop more effective methods for cancer study.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 32%
Student > Master 3 16%
Student > Bachelor 2 11%
Professor > Associate Professor 2 11%
Student > Doctoral Student 2 11%
Other 4 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 37%
Computer Science 3 16%
Agricultural and Biological Sciences 3 16%
Mathematics 2 11%
Medicine and Dentistry 2 11%
Other 2 11%

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 26 June 2018.
All research outputs
#10,472,326
of 13,138,880 outputs
Outputs from BioData Mining
#202
of 233 outputs
Outputs of similar age
#200,920
of 268,683 outputs
Outputs of similar age from BioData Mining
#1
of 1 outputs
Altmetric has tracked 13,138,880 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 233 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 6th percentile – i.e., 6% 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 268,683 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them