Overcoming class imbalance in drug discovery problems: Graph neural networks and balancing approaches-Reference-Cited by-同舟云学术

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Overcoming class imbalance in drug discovery problems: Graph neural networks and balancing approaches

Published:2024-01 Issue: Volume:126 Page:108627
ISSN:1093-3263
Container-title:Journal of Molecular Graphics and Modelling
language:en
Short-container-title:Journal of Molecular Graphics and Modelling

Author:

Almeida Rafael Lopes,Maltarollo Vinícius Gonçalves,Coelho Frederico Gualberto Ferreira

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Elsevier BV

Subject

Materials Chemistry,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Spectroscopy

Reference37 articles.

1. Estimated research and development investment needed to bring a new medicine to market, 2009–2018;Wouters;JAMA,2020

2. Computer aided drug design: an overview;Surabhi;J. Drug Deliv. Ther.,2018

3. An updated review of computer-aided drug design and its application to COVID-19;Gurung;BioMed Res. Int.,2021

4. AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor;Ren;Chem. Sci.,2023

5. Deep machine learning for computer-aided drug design;Bajorath;Front. Drug Discov.,2022

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Addressing class-imbalance challenges in cross-lingual aspect-based sentiment analysis: Dynamic weighted loss and anti-decoupling;Expert Systems with Applications;2024-12

2. Improving the performance of deep learning models in predicting and classifying gamma passing rates with discriminative features and a class balancing technique: a retrospective cohort study;Radiation Oncology;2024-07-31

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