How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions

Kobra Rabiei, Grzegorz A. Rempala, Reinhard Laubenbacher, Wenrui Hao

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DOI: 10.1007/s11538-026-01744-x
Published: 2026-09-03
Container: Bulletin of Mathematical Biology
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s11538-026-01744-x,
  title = {How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions},
  author = {Kobra Rabiei and Grzegorz A. Rempala and Reinhard Laubenbacher and Wenrui Hao},
  year = {2026},
  journal = {Bulletin of Mathematical Biology},
  doi = {10.1007/s11538-026-01744-x},
  url = {https://doi.org/10.1007/s11538-026-01744-x}
}

RIS

TY  - JOUR
TI  - How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions
AU  - Kobra Rabiei
AU  - Grzegorz A. Rempala
AU  - Reinhard Laubenbacher
AU  - Wenrui Hao
PY  - 2026
JO  - Bulletin of Mathematical Biology
DO  - 10.1007/s11538-026-01744-x
UR  - https://doi.org/10.1007/s11538-026-01744-x
ER  -

APA

Rabiei, K., Rempala, G. A., Laubenbacher, R., & Hao, W. (2026). How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions. Bulletin of Mathematical Biology. https://doi.org/10.1007/s11538-026-01744-x

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crossref · retrieved 2026-11-10T11:03:06.714Z