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Development of a Method to Implement Whole-Genome Bisulfite Sequencing of cfDNA from Cancer Patients and a Mouse Tumor Model

Overview of attention for article published in Frontiers in Genetics, January 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

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5 X users
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1 patent

Citations

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22 Dimensions

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71 Mendeley
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Title
Development of a Method to Implement Whole-Genome Bisulfite Sequencing of cfDNA from Cancer Patients and a Mouse Tumor Model
Published in
Frontiers in Genetics, January 2018
DOI 10.3389/fgene.2018.00006
Pubmed ID
Authors

Elaine C. Maggi, Silvia Gravina, Haiying Cheng, Bilal Piperdi, Ziqiang Yuan, Xiao Dong, Steven K. Libutti, Jan Vijg, Cristina Montagna

Abstract

The goal of this study was to develop a method for whole genome cell-free DNA (cfDNA) methylation analysis in humans and mice with the ultimate goal to facilitate the identification of tumor derived DNA methylation changes in the blood. Plasma or serum from patients with pancreatic neuroendocrine tumors or lung cancer, and plasma from a murine model of pancreatic adenocarcinoma was used to develop a protocol for cfDNA isolation, library preparation and whole-genome bisulfite sequencing of ultra low quantities of cfDNA, including tumor-specific DNA. The protocol developed produced high quality libraries consistently generating a conversion rate >98% that will be applicable for the analysis of human and mouse plasma or serum to detect tumor-derived changes in DNA methylation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 27%
Researcher 15 21%
Student > Master 8 11%
Student > Postgraduate 4 6%
Student > Bachelor 3 4%
Other 5 7%
Unknown 17 24%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 22 31%
Medicine and Dentistry 9 13%
Agricultural and Biological Sciences 8 11%
Immunology and Microbiology 2 3%
Computer Science 2 3%
Other 7 10%
Unknown 21 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 28 May 2020.
All research outputs
#6,216,596
of 23,018,998 outputs
Outputs from Frontiers in Genetics
#1,826
of 12,073 outputs
Outputs of similar age
#127,406
of 441,019 outputs
Outputs of similar age from Frontiers in Genetics
#26
of 109 outputs
Altmetric has tracked 23,018,998 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 12,073 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 84% 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 441,019 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 70% of its contemporaries.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.