AI in drug discovery
- Author
- Djork-Arné Clevert, Michael Wand, Kristína Malinovská, Jürgen Schmidhuber and Igor V. Tetko
- Publication Year
- 2025
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Computer Science
- Download Book Read book
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
Keywords: Big data / Deep learning / Drug discovery / Convolution neural networks toxicity / Synthesis planning / Chemo-informatics / GNNs / Ttransformers / Explainable AI / Active learning / Feature decomposition / Solvent effects / Molecular property prediction / Convergent routes / Structure-based drug discovery / Constraints
