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Empowering beginners in bioinformatics with ChatGPT.
Shue, Evelyn; Liu, Li; Li, Bingxin; Feng, Zifeng; Li, Xin; Hu, Gangqing.
Afiliación
  • Shue E; Department of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, WV 26506, USA.
  • Liu L; College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
  • Li B; Biodesign Institute, Arizona State University, Tempe, AZ 85281, USA.
  • Feng Z; Finance Department, John Chambers College of Business and Economics, West Virginia University, Morgantown, WV 26506, USA.
  • Li X; Department of Economics and Finance, The University of Texas at El Paso, El Paso, TX 79902, USA.
  • Hu G; Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA.
Quant Biol ; 11(2): 105-108, 2023 Jun.
Article en En | MEDLINE | ID: mdl-37378043
ABSTRACT
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 chatbot 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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Quant Biol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Quant Biol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos