Text mining techniques have been proposed for extracting protein names and their interactions from biological text. First, we have made improvements on existing methods for handling single word protein names consisting of characters, special symbols, and numbers. Second, compound word protein names are also extracted using conditional probabilities of the occurrences of neighboring words. Third, interactions are extracted based on Bayes theorem over discriminating verbs that represent the interactions of proteins. Experimental results demonstrate the feasibility of our approach with improved performance in terms of accuracy and F-measure, requiring significantly less amount of computational time. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Hong, K., Park, J., Yang, J., & Paek, E. (2005). Automatic extraction of proteins and their interactions from biological text. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3735 LNAI, pp. 322–329). Springer Verlag. https://doi.org/10.1007/11563983_27
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