In the latest years, the application of deep generative models to suggest virtual compounds
is becoming a new and powerful tool in drug discovery projects. The idea behind this review …

Ligand-based drug design has recently benefited from the development of deep generative
models. These models enable extensive explorations of the chemical space and provide a …

Meaningful exploration of the chemical space of druglike molecules in drug design is a
highly challenging task due to a combinatorial explosion of possible modifications of …

Deep generative models are used to generate arbitrary molecular structures with the desired
chemical properties. MolGAN is a renowned molecular generation models that uses …

Across scientific domains, generating new models or optimizing existing ones while meeting
specific criteria is crucial. Traditional machine learning frameworks for guided design use a …

化学の研究開発ではマテリアルズインフォマティクス (機械学習・深層学習を用いた新素材探索や
新材料設計) の技術が導入され始めています. 一方で, 有機化学・無機化学のどの領域かによって …