Details

Autor(en) / Beteiligte

• Ilnicka, Agnieszka
• Schneider, Gisbert

Titel

Designing molecules with autoencoder networks

Ist Teil von

• Nature Computational Science, 2023-11, Vol.3 (11), p.922

Ort / Verlag

United States

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• Autoencoders are versatile tools in molecular informatics. These unsupervised neural networks serve diverse tasks such as data-driven molecular representation and constructive molecular design. This Review explores their algorithmic foundations and applications in drug discovery, highlighting the most active areas of development and the contributions autoencoder networks have made in advancing this field. We also explore the challenges and prospects concerning the utilization of autoencoders and the various adaptations of this neural network architecture in molecular design.