Single Particle

Single particle analysis focuses on determining the three-dimensional structure and dynamics of individual nanoscale particles, primarily biomolecules, from various imaging modalities like X-ray free-electron lasers (XFELs) and cryo-electron microscopy (cryo-EM). Current research heavily utilizes machine learning, particularly deep convolutional neural networks, to address challenges such as noise reduction, particle detection and orientation estimation, and efficient classification of diffraction patterns from massive datasets. These advancements enable higher-resolution structural determination and faster data processing, significantly impacting fields like structural biology and materials science by providing insights into the structure and function of biological macromolecules and nanomaterials under near-physiological conditions.