Chemical information disseminated in scientific documents offers an untapped potential for
deep learning-assisted insights and breakthroughs. Automated extraction efforts have …

The exploration of transition state (TS) geometries is crucial for elucidating chemical reaction
mechanisms and modeling their kinetics. Recently, machine learning (ML) models have …

Diffusion models have swiftly taken the lead in generative modeling, establishing
unprecedented standards for producing high-quality, varied outputs. Unlike Generative …

Identifying bioactive conformations of small molecules is an essential process for virtual
screening applications relying on three-dimensional structure such as molecular docking …

Melanoma is the fifth most common cancer in the United States. Conventional drug
discovery methods are inherently time-consuming and costly, which imposes significant …

Developing molecular generative models for directly generating 3D conformation has
recently become a hot research area. Here, an autoencoder based generative model was …