Molecule Representation

Molecule representation focuses on encoding the complex structural and chemical information of molecules into numerical or graphical formats suitable for machine learning algorithms. Current research emphasizes developing robust representations that capture both 2D topological and 3D geometric features, often using multi-modal approaches and incorporating contextual information from related molecules to improve model performance. These improved representations are crucial for accelerating drug discovery, enabling more efficient optimization of molecular properties and enhancing the accuracy of predictions in various applications, such as virtual screening and property prediction. The ultimate goal is to leverage these advancements to significantly improve the speed and efficiency of drug development and materials science.