一种基于特征点匹配的生物大分子装配方法
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  • 英文篇名:A REPRESENTATION OF FEATURE POINTS IN MACROMOLECULE ASSEMBLY PROBLEM
  • 作者:路建波 ; 张世华 ; 马旭 ; 卢本卓
  • 英文作者:Lu Jianbo;Zhang Shihua;Ma Xu;Lu Benzhuo;National Center for Human Genetics, National Research Institute for Family Planning;Institute of Applied Mathematics, Academy of Mathematics and System Sciences,Chinese Academy of Sciences;LSEC, Institute of Computational Mathematics, Academy of Mathematics and System Sciences,Chinese Academy of Sciences;
  • 关键词:低温电镜 ; 高斯曲率 ; 特征点 ; 生物大分子装配 ; 优化模型
  • 英文关键词:cryo-EM;;Gaussian curvature;;feature points;;biomacromolecules assemly;;Optimization model
  • 中文刊名:SZJS
  • 英文刊名:Journal on Numerical Methods and Computer Applications
  • 机构:国家卫生计生委科学技术研究所,人类遗传资源中心;中国科学院数学与系统科学研究院,应用数学研究所;LSEC,中国科学院数学与系统科学研究院,计算数学与科学工程计算研究所;
  • 出版日期:2017-06-14
  • 出版单位:数值计算与计算机应用
  • 年:2017
  • 期:v.38
  • 基金:国家重点研究发展计划2016YFC1000307和2016YFB0201304;国家重点研究发展计划子课题2016YFC1000307-10;; 国家自然科学基金(21573274);; 国家卫生计生委科学技术研究所科技创新基金面上项目(2017GJM04)
  • 语种:中文;
  • 页:SZJS201702007
  • 页数:12
  • CN:02
  • ISSN:11-2124/TP
  • 分类号:77-88
摘要
研究高分辨率的大分子三维结构,对于分析研究其功能和生物代谢路径具有很重要作用.许多大分子结构可以由低温电镜得到,然而低温电镜三维重构得到的三维结构仍然需要进一步提高其分辨率,所以这些结构仍然需要具体信息.大分子的单独组成部分可以通过结晶、NMR、或者蛋白质结构比较等方法得到.如何将这些高分辨率的组成部分正确装配到大分子结构中是一个很复杂的问题.该问题的实质可以理解为图像处理.在生物大分子的装配过程中,大部分研究者都会用到特征点的方法.现有的研究方法几乎都是基于几何体内的特征点,本文提出一种新的基于蛋白质和低温电镜密度图的表面高斯曲率的方法结合优化模型,对该问题进行研究.数值实验表明,我们的方法是有效的.
        The study of high-resolution three-dimensional macromolecule structure plays an important role in the analysis of the function and metabolic pathways. Many macromolecule structures can be obtained by cryo-EM density maps. But high-resolution three-dimensional structures are still difficult to achieve. On the other hand, The individual components of macromolecules can be obtained by crystallization, NMR, or protein structure comparison.How to properly fit these high-resolution components into macromolecules is a very complicated problem. This problem can be described as image processing problem. In the process of assembly of biological macromolecules, The feature points method is used by most researchers. The existing research methods are always based on the feature points within the geometry, In this paper, we propose a new method which uses the Gaussian curvature of the geometric surface and the optimizing model. Numerical experiments show that our method is effective.
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