Ensemble techniques for predictive modeling of leishmanial activity via molecular fingerprints
Furthermore, the proposed approach has the potential to serve as a framework for addressing other overlooked tropical diseases, offering a promising alternative to conventional drug discovery methods and their associated difficulties.
Authors
- Saif Nalband (ORCID: https://orcid.org/0000-0001-5118-168X)
- Murari Lal Gambhir
- A. Amalin Prince (ORCID: https://orcid.org/0000-0002-4471-9979)
- Ghanshyam Das Gupta (ORCID: https://orcid.org/0000-0002-5377-1082)
- F. Robert (ORCID: https://orcid.org/0000-0002-6143-6372)
- Surabhi Sonam (ORCID: https://orcid.org/0000-0003-3922-731X)
- Pallavi Kiratkar
Institutions
- SRM Institute of Science and Technology (IN)
- Thapar Institute of Engineering & Technology (IN)
- Indian Institute of Science Education and Research Pune (IN)
- D Y Patil International University (IN)
- Birla Institute of Technology and Science, Pilani - Goa Campus (IN)
- Birla Institute of Technology and Science, Pilani (IN)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s12911-025-03041-4
- Primary Topic
- Research on Leishmaniasis Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00