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Bioinformatics and biomedical informatics with ChatGPT: Year one review
Jinge Wang1, Zien Cheng1, Qiuming Yao2
1Department of Microbiology, Immunology & Cell Biology, West Virginia University, Morgantown, West Virginia, USA.
Quantitative Biology (Beijing, China)
|October 4, 2024
Summary
In 2023, large language model chatbots like ChatGPT saw increased use in bioinformatics. This survey reviews ChatGPT applications, highlighting its strengths and limitations in the field.
Area of Science:
- Bioinformatics and Biomedical Informatics
Background:
- Large language models (LLMs) and chatbots, particularly Chat Generative Pre-trained Transformer (ChatGPT), gained prominence in 2023.
- The application of these advanced AI tools across scientific disciplines has seen a significant surge.
Purpose of the Study:
- To comprehensively survey the applications of ChatGPT in bioinformatics and biomedical informatics during 2023.
- To identify the current capabilities and constraints of ChatGPT within this scientific domain.
- To provide insights into future research and development directions for AI in bioinformatics.
Main Methods:
- A systematic review of literature and research publications from 2023 focusing on ChatGPT applications in bioinformatics.
- Categorization of applications across key areas including omics, genetics, text mining, drug discovery, image analysis, programming, and education.
- Analysis of reported successes, challenges, and limitations encountered during implementation.
Main Results:
- ChatGPT has been explored across diverse bioinformatics areas: omics data analysis, genetic variant interpretation, biomedical text mining, accelerating drug discovery, aiding in biomedical image understanding, assisting with bioinformatics programming tasks, and enhancing bioinformatics education.
- Identified strengths include natural language processing capabilities for text-based tasks and code generation assistance.
- Key limitations involve potential inaccuracies, data privacy concerns, and the need for expert validation.
Conclusions:
- ChatGPT presents a powerful, albeit nascent, tool for bioinformatics and biomedical informatics.
- Further research is needed to refine its accuracy, address ethical considerations, and integrate it more robustly into research workflows.
- The potential for AI, specifically LLMs, to revolutionize bioinformatics is substantial, necessitating continued exploration and development.
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