Cargando…
Protein–ligand binding affinity prediction exploiting sequence constituent homology
MOTIVATION: Molecular docking is a commonly used approach for estimating binding conformations and their resultant binding affinities. Machine learning has been successfully deployed to enhance such affinity estimations. Many methods of varying complexity have been developed making use of some or al...
Autores principales: | Abdel-Rehim, Abbi, Orhobor, Oghenejokpeme, Hang, Lou, Ni, Hao, King, Ross D |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463547/ https://www.ncbi.nlm.nih.gov/pubmed/37572302 http://dx.doi.org/10.1093/bioinformatics/btad502 |
Ejemplares similares
-
A simple spatial extension to the extended connectivity interaction features for binding affinity prediction
por: Orhobor, Oghenejokpeme I., et al.
Publicado: (2022) -
Batched Bayesian
Optimization for Drug Design in Noisy
Environments
por: Bellamy, Hugo, et al.
Publicado: (2022) -
Federated Ensemble Regression Using Classification
por: Orhobor, Oghenejokpeme I., et al.
Publicado: (2020) -
An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat
por: Grinberg, Nastasiya F., et al.
Publicado: (2019) -
Generating Explainable and Effective Data Descriptors Using Relational Learning: Application to Cancer Biology
por: Orhobor, Oghenejokpeme I., et al.
Publicado: (2020)