Efficient Segmentation for Cryo-EM Density Maps
Cryo-Electron Microscopy (cryo-EM) is a powerful technique to produce volumetric images of large molecules. The images produced at near-atomic (<5A° ) resolution can be used to determine the structure of those molecules. Due to experimental difficulties including time consuming and high cost, only small portion of the images are produced at near-atomic resolution while the dominant number of available images is produced at sub/nanometer resolution. Protein is a macromolecule composed of amino acids with unique side chain. To determine the structure of protein from Cryo-EM images, segmentation plays an important role in this research. Traditionally, segmentation of cryo-EM density map has been achieved by endless and biased manual process as a result of relative low resolution of the density map. In this research project, we developed a new algorithm based on watershed method and improved square-root divide and conquer algorithm to achieve the object of segmentation of protein.
"Efficient Segmentation for Cryo-EM Density Maps"
ETD Collection for Tennessee State University.