@inproceedings{cf297aed6cf0416590889d0d947926da,
title = "Identifying gene-disease associations using word proximity and similarity of Gene Ontology terms",
abstract = "Associating genes with diseases is an active area of research because it is useful for helping human health with applications to clinical diagnosis and therapy. This paper proposes two methods to guide the associations between genes and diseases: (1) making use of the proximity relationship between genes and diseases and (2) utilizing GO terms shared by genes and diseases for similarity comparison. The experiments show that associations utilizing GO terms perform better than using word proximity. The results reveal that the GO terms act as a good gene-disease association feature.",
keywords = "Gene Ontology, bioinformatics, gene-disease association, text mining, word proximity relationship",
author = "Hou, {Wen Juan} and Chen, {Li Che} and Lu, {Chieh Shiang}",
year = "2011",
doi = "10.1109/BMEI.2011.6098702",
language = "English",
isbn = "9781424493524",
series = "Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011",
pages = "1748--1752",
booktitle = "Proceedings - 2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011",
note = "2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011 ; Conference date: 15-10-2011 Through 17-10-2011",
}
