Clustering Analysis for Vasculitic Diseases
We introduce knowledge discovery for vasculitic diseases in this paper. Vasculitic diseases affect some organs and tissues and diagnosing can be quite difficult. Biomedical literature can contain hidden and useful knowledge for biomedical research and we develop a study based on co-occurrence analysis by using the articles in MEDLINE which is a widely used database.The mostly seen vasculitic diseases are selected to explore hidden patterns. We select PolySearch system as a web based biomedical text mining tool to find organs and tissues in the articles and create two separate datasets with their frequencies for each disease. After forming these datasets, we apply hierarchical clustering analysis to find similarities between the diseases. Clustering analysis reveals some similarities between diseases. We think that the results of clustered diseases positively affect on the medical research of vasculitic diseases especially during the diagnosis and certain similarities can provide different views to medical specialists.
KeywordsBiomedical text mining data mining clustering analysis vasculitic diseases
Unable to display preview. Download preview PDF.
- 3.Vasculitis Foundation Canada, http://www.vasculitis.ca/
- 4.Vasculitis Foundation, http://www.vasculitisfoundation.org/node/1589
- 6.Zhou, W., Smalheiser, N.R., Yu, C.: A tutorial on information retrieval: basic terms and concepts. Journal of Biomedical Discovery and Collaboration 1(2) (2006)Google Scholar
- 7.United States National Library of Medicine (NLM), http://www.nlm.nih.gov/databases/databases_medline.html
- 12.Jelier, R., Schuemie, M.J., Veldhoven, A., Dorssers, L.C., Jenster, G., Kors, G.J.A.: Anni 2.0: a multipurpose text-mining tool for the life sciences. Genome Biology 9(6) (2008)Google Scholar
- 13.Tsuruoka, Y., Tsujii, J., Ananiadou, S.: FACTA: a text search engine for finding associated biomedical concepts. Bioinformatics Applications Note 24(21), 2559–2560 (2008)Google Scholar
- 15.Holland, S.M.: Cluster Analysis. Depatrment of Geology, University of Georgia, Athens, GA 30602-2501 (2006)Google Scholar
- 17.Tan, P.N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Addison Wesley, Reading (2006)Google Scholar
- 18.Open Source Clustering Software, overview, http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/cluster/
- 19.Astikainen, K., Kaven, R.: Statistical Analysis of Array Data:-Dimensionality Reduction, Clustering. Research Seminar on Data Analysis for BioinformaticsGoogle Scholar
- 20.Sato, E.I., Coelho Andrade, L.E.: Systemic vasculitis: a difficult diagnosis. Sao Paulo Med. J. 115(3) (1997)Google Scholar
- 22.Merck, http://www.merck.com