Cargando…
MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules
Artificial intelligence (AI)-based molecular design methods, especially deep generative models for generating novel molecule structures, have gratified our imagination to explore unknown chemical space without relying on brute-force exploration. However, whether designed by AI or human experts, the...
Autores principales: | Liu, Xiaohong, Zhang, Wei, Tong, Xiaochu, Zhong, Feisheng, Li, Zhaojun, Xiong, Zhaoping, Xiong, Jiacheng, Wu, Xiaolong, Fu, Zunyun, Tan, Xiaoqin, Liu, Zhiguo, Zhang, Sulin, Jiang, Hualiang, Li, Xutong, Zheng, Mingyue |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082991/ https://www.ncbi.nlm.nih.gov/pubmed/37031191 http://dx.doi.org/10.1186/s13321-023-00711-1 |
Ejemplares similares
-
Multi-instance learning of graph neural networks for aqueous pK(a) prediction
por: Xiong, Jiacheng, et al.
Publicado: (2021) -
Drug target inference by mining transcriptional data using a novel graph convolutional network framework
por: Zhong, Feisheng, et al.
Publicado: (2021) -
An inductive graph neural network model for compound–protein interaction prediction based on a homogeneous graph
por: Wan, Xiaozhe, et al.
Publicado: (2022) -
Evaluation of GAN-Based Model for Adversarial Training
por: Zhao, Weimin, et al.
Publicado: (2023) -
Mol-CycleGAN: a generative model for molecular optimization
por: Maziarka, Łukasz, et al.
Publicado: (2020)