Algorithms Vs Viruses

Authors

  • Lucio Nájera-Maldonado Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Carpio y Plan de Ayala S/N, Colonia Santo Tomás, 11340, Ciudad de México, México. Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Instituto Politécnico Nacional, Boulevard de la Tecnología, 1036 Z-1, P 2/2, 62790, Xochitepec, Morelos, México.
  • Cristian G. Delgado-Corona Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Carpio y Plan de Ayala S/N, Colonia Santo Tomás, 11340, Ciudad de México, México. Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Instituto Politécnico Nacional, Boulevard de la Tecnología, 1036 Z-1, P 2/2, 62790, Xochitepec, Morelos, México.
  • Francisca Villanueva-Flores Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Instituto Politécnico Nacional, Boulevard de la Tecnología, 1036 Z-1, P 2/2, 62790, Xochitepec, Morelos, México.

Keywords:

Artificial intelligence, vaccines, viruses, algorithms, personalized medicine

Abstract

What if I told you that when a new virus appears, the first to react aren’t just doctors and scientists, but algorithms too? Today, computers can read a virus’s “DNA” as if it were a secret code and, in just a few days, suggest ideas for new vaccines that used to take years. This article, using real-world examples (COVID-19 and malaria), explains how artificial intelligence is becoming an ally in combating infections and could change how we protect ourselves in the future.

References

Barnsley, G., et al. (2024). Impact of the 100 days mission for vaccines on COVID-19: A mathematical modelling study. The Lancet Global Health, 12(11), e1764–e1774. https://doi.org/10.1016/S2214-109X(24)00286-9

Kumar, A., Dixit, S., Srinivasan, K., D., M., & Vincent, P. M. D. R. (2024). Personalized cancer vaccine design using AI-powered technologies. Frontiers in Immunology, 15, 1357217. https://doi.org/10.3389/fimmu.2024.1357217

Lokras, A. G., Bobak, T. R., Baghel, S. S., Sebastiani, F., & Foged, C. (2024). Advances in the design and delivery of RNA vaccines for infectious diseases. Advanced Drug Delivery Reviews, 213, 115419. https://doi.org/10.1016/j.addr.2024.115419

Villanueva-Flores, F., Sanchez-Villamil, J. I., & Garcia-Atutxa, I. (2025). AI-driven epitope prediction: A systematic review, comparative analysis, and practical guide for vaccine development. NPJ Vaccines, 10(1), 207. https://doi.org/10.1038/s41541-025-01258-y

Reynisson, B., Alvarez, B., Paul, S., Peters, B., & Nielsen, M. (2020). NetMHCpan-4.1 and NetMHCIIpan-4.0: Improved predictions of MHC antigen presentation by concurrent motif deconvolution and integration of MS MHC eluted ligand data. Nucleic Acids Research, 48(W1), W449–W454. https://doi.org/10.1093/nar/gkaa379

Kaczanowski, S. (2023). Detection of positive selection acting on protein surfaces at the whole-genome scale in the human malaria parasite Plasmodium falciparum. Infection, Genetics and Evolution, 107, 105397. https://doi.org/10.1016/j.meegid.2022.105397

Downloads

Published

2026-04-13

How to Cite

Nájera-Maldonado, L., Delgado-Corona, C. G., & Villanueva-Flores, F. (2026). Algorithms Vs Viruses. Revista De divulgación científica IBIO, 8(2), 318. Retrieved from https://revistaibio.com/ojs33/index.php/main/article/view/318

Issue

Vol. 8 No. 2 (2026)

Section

Hot Science

License

Copyright (c) 2026 Revista de divulgación científica iBIO

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Self-archiving or deposit of the works in their post-publication version (editorial version) is permitted in any personal, institutional or thematic repository, social or scientific networks. The above applies from the moment of publication of the article in question on the website of the Revista de divulgación científica iBIO.

Most read articles by the same author(s)

1 2 > >>