Chemistry for Space Group Symmetry beyond Crystals.

This document discusses the prediction of crystal systems or space groups using machine learning based on databases. It highlights the development of algorithms for predicting space groups from chemical composition, with a focus on their application in powder X-ray diffraction analysis. The document also explores the statistics of space groups for inorganic and organic crystals, as well as the differences in databases for inorganic compounds, organic compounds, and protein crystallography. It concludes by discussing the influence of molecular and supramolecular symmetry on the symmetry of supramolecular aggregations and the potential for future developments in theories and data utilization methods. [Extracted from the article]