Cargando…
Biological Activity Predictions of Ligands Based on Hybrid Molecular Fingerprinting and Ensemble Learning
[Image: see text] The biological activity predictions of ligands are an important research direction, which can improve the efficiency and success probability of drug screening. However, the traditional prediction method has the disadvantages of complex modeling and low screening efficiency. Machine...
Autores principales: | Li, Mengshan, Zeng, Ming, Zhang, Hang, Chen, Huijie, Guan, Lixin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
|
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9933080/ https://www.ncbi.nlm.nih.gov/pubmed/36816680 http://dx.doi.org/10.1021/acsomega.2c06944 |
Ejemplares similares
-
Prediction of the
Aqueous Solubility of Compounds
Based on Light Gradient Boosting Machines with Molecular Fingerprints
and the Cuckoo Search Algorithm
por: Li, Mengshan, et al.
Publicado: (2022) -
A lncRNA-disease association prediction model based on the two-step PU learning and fully connected neural networks
por: Biyu, Hou, et al.
Publicado: (2023) -
Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods
por: Li, Mengshan, et al.
Publicado: (2018) -
Ensemble learning for prediction of the bioactivity capacity of herbal medicines from chromatographic fingerprints
por: Chen, Hao, et al.
Publicado: (2015) -
CarcinoPred-EL: Novel models for predicting the carcinogenicity of chemicals using molecular fingerprints and ensemble learning methods
por: Zhang, Li, et al.
Publicado: (2017)