PROCESSING OF HIGH RESOLUTION ELECTRON MICROGRAPHS

多年来，我们开发了几种计算技术，用于 生物电子显微照片组的统计分析 大分子。这些方法包括各种类型的阶乘 分析(对应分析、主成分分析)、异常值 定量评估的检测方案和统计标准 空间分辨率(光谱信噪比)，以及快速的 确定两个变量之间比例因子的算法 显微照片。 目前的目标是能够组合更多数量的显微照片 放大倍数略有不同，以便获得 二十面体病毒的高分辨率三维重建。为了这个 目的，我们正在开发新的基于样条的算法，用于各种 几何校正(任意缩放、平移和旋转)。 这些方法都是基于一般的最小二乘原理。

Over the years, we have developed several computational techniques for the statistical analysis of sets of electron micrographs of biological macromolecules. These methods include various types of factorial analysis (correspondence analysis, principal components), outlier detection schemes, statistical criteria for the quantitative assessment of spatial resolution (spectral signal-to-noise ratios), and a fast algorithm for the determination of the scaling factors between two micrographs. A current goal is to be able to combine a larger number of micrographs with slight disparities in magnification, in order to obtain higher-resolution 3-D reconstructions of icosahedral viruses. For this purpose, we are developing new spline-based algorithms for various geometric corrections (arbitrary scaling, translation, and rotation). These methods are based on a general least squares principle.