Sigworth Fred J
Department of Cellular and Molecular Physiology, Yale University, 333 Cedar Street, New Haven, CT 06520, USA.
J Struct Biol. 2004 Jan-Feb;145(1-2):111-22. doi: 10.1016/j.jsb.2003.10.025.
Particle selection is an essential but tedious step in the determination of macromolecular structures by single particle reconstruction. This paper presents an automatic, multi-reference particle detection scheme that is based on the classical matched filter principle. It makes use of a pre-whitening filter to standardize the noise, a reduced representation of the references by means of principal component analysis, and a statistic for distinguishing particles from image artifacts. Standardizing the noise allows the noise-induced false-positive frequency to be estimated, and also allows the distribution of the discrimination statistic to be calculated a priori. The method is demonstrated with an annotated dataset of cryo-EM images.
在通过单颗粒重建确定大分子结构的过程中，颗粒选择是一个必不可少但又很繁琐的步骤。本文提出了一种基于经典匹配滤波器原理的自动多参考颗粒检测方案。它利用预白化滤波器来标准化噪声，通过主成分分析对参考进行降维表示，并采用一种统计量来区分颗粒与图像伪影。对噪声进行标准化使得能够估计由噪声引起的误报频率，还能预先计算判别统计量的分布。该方法通过一个带有注释的冷冻电镜图像数据集进行了验证。
