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Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends

Overview of attention for article published in BMC Research Notes, April 2016
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Mentioned by

twitter
2 tweeters

Citations

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19 Dimensions

Readers on

mendeley
95 Mendeley
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Title
Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends
Published in
BMC Research Notes, April 2016
DOI 10.1186/s13104-016-2023-5
Pubmed ID
Authors

Gabriela Jurca, Omar Addam, Alper Aksac, Shang Gao, Tansel Özyer, Douglas Demetrick, Reda Alhajj

Abstract

Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters 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 95 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 1%
Italy 1 1%
Unknown 93 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 14%
Student > Ph. D. Student 9 9%
Student > Master 9 9%
Student > Postgraduate 8 8%
Student > Bachelor 8 8%
Other 28 29%
Unknown 20 21%
Readers by discipline Count As %
Computer Science 17 18%
Medicine and Dentistry 12 13%
Agricultural and Biological Sciences 9 9%
Biochemistry, Genetics and Molecular Biology 8 8%
Social Sciences 6 6%
Other 17 18%
Unknown 26 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 13 June 2016.
All research outputs
#3,908,745
of 7,890,722 outputs
Outputs from BMC Research Notes
#894
of 1,932 outputs
Outputs of similar age
#134,167
of 268,998 outputs
Outputs of similar age from BMC Research Notes
#41
of 90 outputs
Altmetric has tracked 7,890,722 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,932 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 49th percentile – i.e., 49% 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 268,998 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.