| 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. |
X Demographics
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 111 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 | 109 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 14% |
| Student > Master | 10 | 9% |
| Student > Bachelor | 10 | 9% |
| Student > Ph. D. Student | 9 | 8% |
| Other | 9 | 8% |
| Other | 28 | 25% |
| Unknown | 30 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 16 | 14% |
| Medicine and Dentistry | 13 | 12% |
| Agricultural and Biological Sciences | 9 | 8% |
| Biochemistry, Genetics and Molecular Biology | 8 | 7% |
| Social Sciences | 7 | 6% |
| Other | 20 | 18% |
| Unknown | 38 | 34% |
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
#14,847,187
of 22,865,319 outputs
Outputs from BMC Research Notes
#2,126
of 4,267 outputs
Outputs of similar age
#169,849
of 298,924 outputs
Outputs of similar age from BMC Research Notes
#50
of 93 outputs
Altmetric has tracked 22,865,319 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,267 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
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We're also able to compare this research output to 93 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.