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Multistage Gene Normalization and SVM-Based Ranking for Protein Interactor Extraction in Full-Text Articles

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3 Author(s)
Hong-Jie Dai ; Dept. of Comput. Sci., Nat. TsingHua Univ., Hsinchu, Taiwan ; Po-Ting Lai ; Tsai, R.T.-H.

The interactor normalization task (INT) is to identify genes that play the interactor role in protein-protein interactions (PPIs), to map these genes to unique IDs, and to rank them according to their normalized confidence. INT has two subtasks: gene normalization (GN) and interactor ranking. The main difficulties of INT GN are identifying genes across species and using full papers instead of abstracts. To tackle these problems, we developed a multistage GN algorithm and a ranking method, which exploit information in different parts of a paper. Our system achieved a promising AUC of 0.43471. Using the multistage GN algorithm, we have been able to improve system performance (AUC) by 1.719 percent compared to a one-stage GN algorithm. Our experimental results also show that with full text, versus abstract only, INT AUC performance was 22.6 percent higher.

Published in:

Computational Biology and Bioinformatics, IEEE/ACM Transactions on  (Volume:7 ,  Issue: 3 )