Evolution of AIGC Technology and Its Applications in Life Sciences

This article reviews the development of AIGC and generative AI technologies—including image, text, and molecular generation—explains key model advances such as diffusion and large language models, discusses their impact on drug discovery, and outlines current challenges, opportunities, and future directions.

AI in Life SciencesAIGCdrug discovery

0 likes · 14 min read

Evolution of AIGC Technology and Its Applications in Life Sciences

DataFunSummit

Apr 11, 2021 · Artificial Intelligence

Applications of Graph Neural Networks in Biochemistry and Drug Discovery

Graph Neural Networks (GNNs) are increasingly applied in biochemistry, enabling molecular property prediction, chemical reaction forecasting, molecular graph generation, and drug–protein interaction modeling, with various generative models such as GraphRNN, MolGAN, VAE, and flow-based approaches enhancing drug discovery pipelines.

AIchemical reaction predictiondrug discovery

0 likes · 17 min read

Applications of Graph Neural Networks in Biochemistry and Drug Discovery