PlayMolecule Glimpse: Understanding Protein–Ligand Property Predictions with Interpretable Neural Networks-Reference-Cited by-同舟云学术

PlayMolecule Glimpse: Understanding Protein–Ligand Property Predictions with Interpretable Neural Networks

Published:2022-01-03 Issue:2 Volume:62 Page:225-231
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Varela-Rial Alejandro¹²^ORCID,Maryanow Iain²,Majewski Maciej¹^ORCID,Doerr Stefan²,Schapin Nikolai¹²,Jiménez-Luna José¹,De Fabritiis Gianni¹²³^ORCID

Affiliation:

1. Computational Science Laboratory, Universitat Pompeu Fabra, Barcelona Biomedical Research Park (PRBB), Carrer Dr. Aiguader 88, 08003 Barcelona, Spain

2. Acellera Labs, Doctor Trueta 183, 08005 Barcelona, Spain

3. Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig Lluis Companys 23, 08010 Barcelona, Spain

Funder

Ministerio de Econom??a, Industria y Competitividad, Gobierno de Espa??a

European Regional Development Fund

Ag??ncia de Gesti?? d???Ajuts Universitaris i de Recerca

H2020 Research Infrastructures

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.1c00691

Reference34 articles.

1. Computational Methods in Developing Quantitative Structure-Activity Relationships (QSAR): A Review

2. QSAR Modeling: Where Have You Been? Where Are You Going To?

3. Machine learning in chemoinformatics and drug discovery

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5. Applications of Machine Learning Methods in Drug Toxicity Prediction

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