¹Faculty of Computer Engineering, Huaiyin Institute of Technology, Huaian 223003, P.R. China
²State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, P.R. China

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Abstract—With the explosion of biological data and information in the omics era, text mining is becoming increasingly crucial for biomedical researchers to find relevant biomedical knowledge. This paper presents an approach for target identification and target-centered network construction from biomedical literature. The approach can identify several types of biomedical targets using finite state machine and ontology-based approach, and offer the implementation of target-centered network which could directly illustrate the relationships among targets. To validate the approach, we developed a system which achieved a recall 79.5%, a precision 83.1%, and an Fscore 81.0% on average for the test datasets. Experimental results show that our approach is promising to develop text mining tool for biomedical researchers.

Index Terms—Target identification; text mining; biomedical ontology; finite state machine; target-centered network.

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Cite: Lejun Gong, Yunyang Yan, Xiao Sun, "Target Identification and Target-centered Network Construction from Biomedical Literature," Journal of Software vol. 8, no. 2, pp. 316-319, 2013.