Wang Jia-Hong, Zhao Ling-Feng, Lin Pei, Su Xiao-Rong, Chen Shi-Jun, Huang Li-Qiang, Wang Hua-Feng, Zhang Hai, Hu Zhen-Fu, Yao Kai-Tai, Huang Zhong-Xi
Cancer Institute, Key Laboratory of Zebrafish Modeling and Drug Screening for Human Diseases of Guangdong Higher Education Institutes, Department of Cell Biology, Southern Medical University, Guangzhou 510515, Guangzhou Biotechnology Center, Guangzhou, 510630, School of Basic Medical Sciences, Network Center and Department of Plastic Surgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China.
Bioinformatics. 2014 Sep 1;30(17):2534-6. doi: 10.1093/bioinformatics/btu241. Epub 2014 Apr 23.
Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms.
Supplementary data are available at Bioinformatics online.
在基因列表中识别生物学功能和分子网络以及这些基因如何与各种主题相关，对生物医学研究人员具有相当大的价值。在此，我们展示了一个基于网络的文本挖掘服务器GenCLiP 2.0，它可以通过丰富的关键词和分子相互作用来分析人类基因。与其他类似工具相比，GenCLiP 2.0具有两个独特的功能：（i）使用文献挖掘产生或用户提供的自由词（即文献中的任何词）分析基因功能，以及（ii）从Medline摘要中准确识别和整合全面的分子相互作用，以构建与自由词相关的分子网络和子网。
补充数据可在《生物信息学》在线获取。
