• Difei Wang, Guannan Chen, Lin Li, Shaodi Wen, Zijing Xie, Xiao Luo, Li Zhan, Shuangbin Xu, Junrui Li, Rui Wang, Qianwen Wang, and Guangchuang Yu.
• Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, China.
• Chin. Med. J. 2024 Aug 20; 137 (16): 195019561950-1956.

AbstractInterpreting genes of interest is essential for identifying molecular mechanisms, but acquiring such information typically involves tedious manual retrieval. To streamline this process, the fanyi package offers tools to retrieve gene information from sources like National Center for Biotechnology Information (NCBI), significantly enhancing accessibility. Additionally, understanding the latest research advancements and sharing achievements are crucial for junior researchers. However, language barriers often restrict knowledge absorption and career development. To address these challenges, we developed the fanyi package, which leverages artificial intelligence (AI)-driven online translation services to accurately translate among multiple languages. This dual functionality allows researchers to quickly capture and comprehend information, promotes a multilingual environment, and fosters innovation in academic community. Meanwhile, the translation functions are versatile and applicable beyond biomedicine research to other domains as well. The fanyi package is freely available at https://github.com/YuLab-SMU/fanyi .Copyright © 2024 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.

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