Odor Descriptor Prediction

Odor Descriptor Prediction is a task that constructs models of the relationship between molecular structure and odor (Structure-Odor Relationships, SOR), aiming to predict the corresponding odor descriptors (such as fruity, musky, etc.) of chemical molecules through their structural characteristics. The goal of this task is to use machine learning algorithms and cheminformatics methods to achieve efficient and accurate prediction of the olfactory properties of unknown molecules. In the medical field, this technology can assist in screening compounds with specific odors during the process of new drug development, enhancing patient acceptance and therapeutic outcomes.