Jia-Hong Wang1, Ling-Feng Zhao1, Pei Lin1, Xiao-Rong Su1, Shi-Jun Chen1, Li-Qiang Huang1, Hua-Feng Wang1, Hai Zhang1, Zhen-Fu Hu1, Kai-Tai Yao1, Zhong-Xi Huang1. 1. 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.
Abstract
UNLABELLED: 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. AVAILABILITY AND IMPLEMENTATION: http://ci.smu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
UNLABELLED: 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. AVAILABILITY AND IMPLEMENTATION: http://ci.smu.edu.cn. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Igor B Rogozin; Abiel Roche-Lima; Kathrin Tyryshkin; Kelvin Carrasquillo-Carrión; Artem G Lada; Lennard Y Poliakov; Elena Schwartz; Andreu Saura; Vyacheslav Yurchenko; David N Cooper; Anna R Panchenko; Youri I Pavlov Journal: Front Genet Date: 2021-05-19 Impact factor: 4.599