A review on machine learning approaches and trends in drug discovery

[Display omitted] •Machine Learning in drug discovery has greatly benefited the pharmaceutical industry.•Application of machine algorithms must entail a robust design in real clinical tasks.•Trending machine learning algorithms in drug design: NB, SVM, RF and ANN. Drug discovery aims at finding new...

Full description

Saved in:

Bibliographic Details
Published in:	Computational and structural biotechnology journal Vol. 19; pp. 4538 - 4558
Main Authors:	Carracedo-Reboredo, Paula, Liñares-Blanco, Jose, Rodríguez-Fernández, Nereida, Cedrón, Francisco, Novoa, Francisco J., Carballal, Adrian, Maojo, Victor, Pazos, Alejandro, Fernandez-Lozano, Carlos
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.01.2021 Research Network of Computational and Structural Biotechnology Elsevier
Subjects:	biotechnology Cheminformatics chemoinformatics computer science Deep Learning Drug Discovery drugs Machine Learning Molecular Descriptors precision medicine QSAR Review ANN Cheminformatics CNN FDA BBB RNA MACCS GNN FNN ECFP DL t-SNE CNS FP Molecular Descriptors CDK SVM Machine Learning FS ADMET ADR AUC MD KEGG ML WHO OOB APFP AI GO SMILES MCC Drug Discovery Deep Learning TCGA PCA MKL GEO CV GCN NB RF QSAR DNA CPI
ISSN:	2001-0370, 2001-0370
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!