Shue Evelyn, Liu Li, Li Bingxin, Feng Zifeng, Li Xin, Hu Gangqing
Department of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, WV, USA.
College of Health Solutions, Arizona State University, Phoenix, AZ, USA.
bioRxiv. 2023 Mar 8:2023.03.07.531414. doi: 10.1101/2023.03.07.531414.
The impressive conversational and programming abilities of ChatGPT make it an attractive tool for facilitating the education of bioinformatics data analysis for beginners. In this study, we proposed an iterative model to fine-tune instructions for guiding a ChatGPT in generating code for bioinformatics data analysis tasks. We demonstrated the feasibility of the model by applying it to various bioinformatics topics. Additionally, we discussed practical considerations and limitations regarding the use of the model in chatbot-aided bioinformatics education.
ChatGPT令人印象深刻的对话和编程能力使其成为促进初学者生物信息数据分析教育的有吸引力的工具。在本研究中,我们提出了一种迭代模型,用于微调指导ChatGPT生成生物信息数据分析任务代码的指令。我们通过将该模型应用于各种生物信息学主题来证明其可行性。此外,我们还讨论了在聊天机器人辅助生物信息学教育中使用该模型的实际考虑因素和局限性。