Predicting toxicity properties through machine learning
It is currently known that the high power of a drug does not fully determine its efficacy. Several properties must also be considered, including absorption, distribution, metabolism, excretion and toxicity [8]. These are the ADME-Tox properties, which are fundamental in the discovery of new effectiv...
- Autores:
-
Borrero, Luz Adriana
Sanchez Guette, Lilibeth
Lopez, Enrique
Pineda, Omar
BUELVAS CASTRO, EDGARDO MANUEL
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7802
- Acceso en línea:
- https://hdl.handle.net/11323/7802
https://doi.org/10.1016/j.procs.2020.03.093
https://repositorio.cuc.edu.co/
- Palabra clave:
- Supervised
unsupervised learning machines
support vector machine (SVM)
artificial neural networks (ANN)
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International