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


RESULTS
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.


CONCLUSIONS
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.
Department of Computer Science, University of Calgary, Calgary, AB, Canada.
Gabriela
G
Jurca
Department of Computer Science, University of Calgary, Calgary, AB, Canada.
Omar
O
Addam
Department of Computer Science, University of Calgary, Calgary, AB, Canada.
Alper
A
Aksac
College of Computer Science and Technology, Jilin University, Changchun, China.
Shang
S
Gao
Department of Computer Engineering, TOBB University, Ankara, Turkey.
Tansel
T
Özyer
Departments of Pathology, Oncology and Biochemistry & Molecular Biology, University of Calgary, Calgary, AB, Canada.
Douglas
D
Demetrick
Department of Computer Science, University of Calgary, Calgary, AB, Canada. alhajj@ucalgary.ca.|Department of Computer Science, Global University, Beirut, Lebanon. alhajj@ucalgary.ca.
Reda
R
Alhajj
D014408:Biomarkers, Tumor / Q000145:classification / Q000235:genetics*; D035843:Biomedical Research / Q000706:statistics & numerical data; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics*; D016000:Cluster Analysis; D057225:Data Mining / Q000379:methods*; D004843:Epistasis, Genetic / Q000235:genetics; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005843:Geography; D006801:Humans; D039781:PubMed / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D060756:Social Networking
D014408:Biomarkers, Tumor
Breast cancer; Data mining; Network analysis; Text mining