MATLAB-RDKit: Cheminformatics and AI-Driven Molecular Discovery
Overview
Cheminformatics is transforming the way chemists explore chemical space, discover new compounds, and accelerate research. Join us for this tutorial webinar to see how MATLAB-RDKit workflow empowers chemists to import, visualize, and analyze molecular data while leveraging the latest advances in artificial intelligence and machine learning. This session will demonstrate practical workflows for handling chemical data, extracting molecular features, and building predictive models using both traditional cheminformatics tools and state-of-the-art AI techniques such as transformers and graph neural networks.
Highlights
- MATLAB-RDKit Workflow: Learn how to manage large molecular datasets, bring in molecular data from common formats (e.g., SDF, SMILES) and partition datasets based on property and structural similarities.
- Molecular Visualization and Analysis: Explore interactive visualization of molecular structures and properties directly in MATLAB, enabling intuitive chemical data exploration.
- AI-Powered Molecular Discovery: See how transformer-based models and graph neural networks can be used for structural and property predictions.
Who Should Attend
- Chemists and Chemical Engineers
- Computational chemists and data scientists working in chemistry or materials science
- Researchers interested in AI and machine learning for molecular discovery
