Exploring antimalarial activity of drugs using weighted atomic vectors and artificial intelligence
The combination of weighted atomic vectors and machine learning emerges as a promising approach for antimalarial pharmaceutical research, emphasizing the significance of artificial intelligence in this field.
Authors
- Juan A. Castillo‐Garit (ORCID: https://orcid.org/0000-0003-0896-9484)
- Stephen J. Barigye (ORCID: https://orcid.org/0000-0003-3547-8293)
- Yoan Martínez‐López (ORCID: https://orcid.org/0000-0002-1950-567X)
- Oscar Martínez‐Santiago (ORCID: https://orcid.org/0000-0003-1921-903X)
- Noel Enrique Rodríguez Maya
- W. Rodriguez
Institutions
- University of Miami (US)
- Instituto Tecnológico de Querétaro (MX)
- Dirección de Investigación y Desarrollo (CL)
- Metropolitan University of Technology (CL)
- Instituto Tecnológico de Zitácuaro
- Universidad Autónoma de Madrid (ES)
- University of Camagüey (CU)
Publication Details
- Journal
- Journal of Vector Borne Diseases
- Published
- 2025-06-09
- DOI
- https://doi.org/10.4103/jvbd.jvbd_131_24
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00