Integrating Text Mining, Data Mining, and Network Analysis to Analyze Biomarker Trends in Prostate Cancer and Breast Cancer

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atmire.migration.oldid5167
dc.contributor.advisorAlhajj, Reda
dc.contributor.authorJurca, Gabriela
dc.contributor.committeememberRokne, Jon
dc.contributor.committeememberWang, Xin
dc.date.accessioned2016-12-22T20:17:53Z
dc.date.available2016-12-22T20:17:53Z
dc.date.issued2016
dc.date.submitted2016en
dc.description.abstractCancer is a serious disease which has many types and affects many people. One goal of biomedical researchers is to find genetic biomarkers for diagnosis and prognosis of cancer. Since there is already a vast amount of scientific publications on cancer, computational methods can be used to find hidden patterns from literature. This thesis presents a framework which investigates existing literature data by integrating text mining, data mining, and network analysis. 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 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 of our results have been validated against results from other tools that predict gene relations and functions.en_US
dc.identifier.citationJurca, G. (2016). Integrating Text Mining, Data Mining, and Network Analysis to Analyze Biomarker Trends in Prostate Cancer and Breast Cancer (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/26581en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/26581
dc.identifier.urihttp://hdl.handle.net/11023/3504
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectBioinformatics
dc.subjectComputer Science
dc.subject.classificationProstate Canceren_US
dc.subject.classificationbreast canceren_US
dc.subject.classificationData Miningen_US
dc.subject.classificationtext miningen_US
dc.subject.classificationnetwork analysisen_US
dc.titleIntegrating Text Mining, Data Mining, and Network Analysis to Analyze Biomarker Trends in Prostate Cancer and Breast Cancer
dc.typemaster thesis
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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