Gene Pathway Text Mining and Visualization
Information Systems and Technology (CGU)
Automatically extracting gene-pathway relations from medical research texts gives researchers access to the latest findings in a structured format. Such relations must be precise to be useful. We present two case studies of approaches used to automatically extract gene-pathway relations from text. Each technique has performed at or near the 90 percent precision level making them good candidates to perform the extraction task. In addition, we present a visualization system that uses XML to interface with the extracted gene-pathway relations. The user-selected relations are automatically presented in a network display, inspired by the pathway maps created by gene researchers manually. Future research involves identification of equivalent relations expressed differently by authors and identification of relations that contradict each other along with the inquiry of how this information is useful to researchers.
© 2005 Springer
D. M. McDonald , H. Su, J. Xu, C.-J. Tseng, H. Chen, and G. Leroy, "Genepathway Text Mining and Visualization," in Medical Informatics: Advances in Knowledge Management and Data Mining in Biomedicine, Eds. H. Chen, S. Fuller, and A. McCray, 2005. doi: 10.1007/0-387-25739-X_18