GAを用いた単粒子解析におけるオイラー角推定

DOI DOI Web Site PubMed
  • Saeki Shusuke
    Graduate School of Frontier Science, The University of Tokyo
  • Asai Kiyoshi
    Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology
  • Takahashi Katsutoshi
    Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology
  • Ueno Yutaka
    Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology
  • Isono Katsunori
    INTEC Web and Genome Informatics Corporation
  • Iba Hitoshi
    Graduate School of Frontier Science, The University of Tokyo

書誌事項

タイトル別名
  • Inference of Euler Angles for Single Particle Analysis by Using Genetic Algorithms
  • GA オ モチイタ タンリュウシ カイセキ ニ オケル オイラーカク スイテイ

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説明

Single particle analysis is one of the methods for structural studies of protein and macromolecules developed in image analysis on electron microscopy. Reconstructing 3D structure from microscope images is not an easy analysis because of the low resolution of images and lack of the directional information of images in 3D structure. To improve the resolution, different projections are aligned, classified and averaged. Inferring the orientations of these images is so difficult that the task of reconstructing 3D structures depends upon the experience of researchers. But recently, a method to reconstruct 3D structures is automatically devised. In this paper, we propose a new method for determining Euler angles of projections by applying Genetic Algorithms (i. e., GAs).We empirically show that the proposed approach has improved the previous one in terms of computational time and acquired precision.

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