GenCLiP 3: mining human genes' functions and regulatory networks from PubMed based on co-occurrences and natural language processing

Author:

Wang Jia-Hong1,Zhao Ling-Feng2,Wang Hua-Feng3,Wen Yue-Ting1,Jiang Kui-Kui4,Mao Xiang-Ming5,Zhou Zi-Ying1,Yao Kai-Tai1,Geng Qing-Shan6,Guo Dan7,Huang Zhong-Xi1

Affiliation:

1. Cancer Research Institute, School of Basic Medical Sciences, Southern Medical University, Guangzhou, P.R China

2. Guangzhou Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou, P.R China

3. Shunde Hospital, Southern Medical University, Foshan, P.R China

4. Department of Medical Oncology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, P. R. China

5. Department of Urology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong, P.R China

6. Guangdong General Hospital, Guangzhou, China

7. Department of Pharmacy, Nanfang Hospital, Southern Medical University, Guangzhou, P.R China

Abstract

Abstract Summary We present a web server, GenCLiP 3, which is an updated version of GenCLiP 2.0 to enhance analysis of human gene functions and regulatory networks, with the following improvements: i) accurate recognition of molecular interactions with polarity and directionality from the entire PubMed database; ii) support for Boolean search to customize multiple-term search and to quickly retrieve function related genes; iii) strengthened association between gene and keyword by a new scoring method; and iv) daily updates following literature release at PubMed FTP. Availability The server is freely available for academic use at: http://ci.smu.edu.cn/genclip3/. Supplementary information Supplementary data are available at Bioinformatics online.

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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