Warning! This email originated from outside of PSB. Do not click links or open attachments unless you recognize the sender and know the content is safe. -------------------------------------- Dear all, On behalf of Martijn Oldenhof and Yves Moreau, I’d like to share the announcement of this seminar of Igor Tetko on Advanced Machine Learning in Drug Discovery. It’ll take place on the 3rd of September between 11-12h - Elektrotechnisch Instituut (335-01), ELEC 01.62, Kasteelpark Arenberg 10 , 3001 Heverlee. More information: https://set.kuleuven.be/phd/seminars/tetko Abstract: Modern Machine Learning (ML) based on deep neural networks (DNNs), which form the basis of Artificial Intelligence (AI), is gaining popularity in the field of drug discovery. These methods can digest large amounts of information and provide reliable predictions for new molecules. Notably, such methods need not rely anymore on descriptors, but can learn their internal representations based on text or molecular graphs. They can also incorporate non-traditional information, such as images produced by high content screening, to better utilize results of in vitro measurements. Emerging solutions include the use of meta- and transfer-learning approaches, which enable the pre-training of models on a large corpus of chemical data of different modalities, and then efficiently applies the models to small datasets. The estimation of the accuracy of such predictions, which allows for the discrimination between reliable vs non-reliable predictions, is another important direction of the development of these methods. Being considered for a long time as black boxes, DNNs can become interpretable via eXplainable AI (XAI) methods. These developments open new perspectives for the use of ML in chemistry. Best regards, Alex