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Achyut Sapkota, Kazunori Hamada (National Institute of Technology, Kisarazu College, 2-11-1, Kiyomidai-Higashi, Kisarazu, Chiba 292-0016 Japan)
There are several studies in biomedical fields and the objectives of these studies are obviously many. In normal literature reviews, people tend to search the studies with similar objectives. However, there can be significant clues in the studies carried with completely different objectives and in completely different scenarios. This study represents an algorithm to extract and visualize the interrelated biological words from the abstract of the articles listed in PUBMED database. A case study has been shown with the disease “Down Syndrome” as a case. We extracted a small sub-network from the network we obtained to represent the biological terms related to Down syndrome. It was able to show mouse models to study Down syndrome (Ts65Dn, Ts1Cje), the human chromosome 21 (HSA21), the major region of study for Down syndrome and its identical chromosome 16 (MMU16) in mouse and other related terms. As we are from informatics background, we ourselves were not familiar to these words related to Down syndrome in the beginning. Our manual literature survey of these and other few related words showed that the extracted words and their relationship were significantly important.