Opportunities and considerations for using artificial intelligence in bioinformatics education
Open accessAbstract
Artificial intelligence (AI) tools and techniques are undoubtedly being used in bioinformatics education, reflecting broader trends in education. However, many instructors and learners may be unaware of the full scope of potential uses for these tools within bioinformatics education, as well as effective practices for using them. Building on discussions held at the 6th Global Bioinformatics Education Summit, this perspective article provides insights about ways that AI might be used to generate or adapt instructional content, provide personalized help for learners, and automate assessment and grading. Additionally, we highlight AI skills that are important for bioinformatics learners to develop in order to effectively use AI as a bioinformatics learning tool. We highlight currently available tools in the quickly evolving AI landscape and suggest ways that instructors or learners might use such tools. Furthermore, we discuss key considerations and challenges associated with integrating AI into bioinformatics education, including ethical implications, potential biases, and the need to critically evaluate AI-generated content. Finally, we highlight the need for further research to better understand how AI tools are being used in practice and empower their effective and responsible use in bioinformatics education.
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Cited by
Sorted by citations
Learning R with generative AI in a metagenomic data science course
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Teaching bioinformatics with generative AI: judgment, uncertainty, and responsibility
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- Authors
- Piccolo, S. R., Nathan, A., Brazas, M. D., Kandpal, M., Miró-Herrans, A. T., Kleinschmit, A. J., McClatchy, S., Mutheiwana, P., Nikolic, D., Gallo, L. I., Julius, R. S., Lloret-Llinares, M., Mulder, N., Presgraves, D., Shewaramani, S., Xool-Tamayo, J., Chain, F. J. J., & Sanchez Guerrero, S. A.
- Affiliations
- Brigham Young University (US)
- Harvard University (US)
- Ontario Institute for Cancer Research (CA)
- Rockefeller University (US)
- University of Florida (US)
- University of Dubuque (US)
- Jackson Laboratory (US)
- University of Cape Town (ZA)
- Wellcome Connecting Science (GB)
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- European Bioinformatics Institute (GB)
- Public Health Agency of Canada (CA)
- Centro de Investigación Científica y de Educación Superior de Ensenada (MX)
- University of Massachusetts Lowell (US)
- Bachillerato Tecnológico de Educación y Promoción Deportiva (BTED), Plantel Tetla de la Solidaridad, Prolongación República de Brasil s/n 2da secc, Teotlalpan, C.P. 90430, Tetla de la Solidaridad, Tlaxcala, México
- Corresponding author
- Piccolo, Stephen R
- Nathan, Aparna
- ORCID
- Venue
- Bioinformatics Advances
- Publisher
- Oxford University Press (OUP)
- Published
- 2024-12-26
- Volume
- 5
- Issue
- 1
- Pages
- vbaf169-vbaf169
- ISSN
- 2635-0041 (ISSN-L)
- PMC
- PMC12401575
- OpenAlex
- W4413890799
- Cited by
- 2
- References
- 31
- Citations by year
- 2026: 2
- FWCI
- 0.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Bioinformatics Advances (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- Funders
- USA National Institutes of Health (R03HL168983)
- USA National Center for Advancing Translational Sciences, National Institutes of Health
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence in education, bioinformatics education, personalized learning, ethical implications of AI, algorithmic bias, critical evaluation of AI-generated content, responsible AI use
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