ASSOCIATION MINING FROM BIOMEDICAL TEXT WITH NETWORK ANALYSIS
- Department of Computer Science and Engineering, College of Engineering Guindy, Anna University, Chennai, India.
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Discovery of genes that are responsible for various diseases, becomes an important task. Since the genes are related with many diseases, the gene-disease association should be discovered. To obtain this gene-disease association from available biomedical literature, the relation type between the gene and disease is extracted from the biomedical literature. So, this becomes more and more important to deal with the extraction problem from the biomedical texts in an automatic way. Then the gene-disease association is visualized by network construction and association score matrix is constructed to calculate the gene-disease association score. The gene-disease relation type is identified and then the association score is calculated by integrating disease similarity network and protein-protein interaction network. The candidate genes for the particular disease and the novel genes for various diseases can also be found by calculating the association score and visualizing the dataset network.
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[Kanimozhi U and Manjula D. (2017); ASSOCIATION MINING FROM BIOMEDICAL TEXT WITH NETWORK ANALYSIS Int. J. of Adv. Res. 5 (Jan). 158-169] (ISSN 2320-5407). www.journalijar.com
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