A one-day conference on Chemical Structure Representations will bring together researchers from academia, industry, and software development to explore how we encode, interpret, and leverage molecular structures in modern chemical science. From classical line notations and connection tables to graph neural networks, learned embeddings, and foundation models, the meeting will examine how representation choices shape prediction, design, synthesis planning, data integration, and regulatory communication.
Talks will span cheminformatics, computational chemistry, AI/ML, structural biology, and drug discovery, with an emphasis on practical impact, interoperability, and reproducibility. By connecting experts in theory, algorithms, and application, the conference aims to catalyse new ideas and collaborations around one of the most fundamental questions in digital chemistry: how we represent molecules determines what we can discover.
Talks will span cheminformatics, computational chemistry, AI/ML, structural biology, and drug discovery, with an emphasis on practical impact, interoperability, and reproducibility. By connecting experts in theory, algorithms, and application, the conference aims to catalyse new ideas and collaborations around one of the most fundamental questions in digital chemistry: how we represent molecules determines what we can discover.
