Quantitative Analysis of Single Molecule Microscopy

项目摘要/摘要 单分子显微镜是一种相对新颖的技术，它允许单个分子 用光学显微镜成像。它引起了科学家的极大兴趣，因为它使 在分子水平上观察细胞过程，这是经典方法无法完成的任务 由于细胞过程被平均和整体遮挡而导致的光学成像方法 效果。基于单分子跟踪和定位的超分辨率显微镜(Palm/Storm) 是单分子成像实验的两个主要例子。这些方面的改进 与传统成像方法相比，技术的精确度直接取决于 可以估计样品中单分子的位置。这导致了两大挑战。 第一，设计实验，以获得尽可能好的数据。二、对中国传统文化的分析 以最优化的方式获取数据。 单分子实验的技术难度在很大程度上是由于非常低的 存在明显噪声源时的光子计数，例如散射光子和照相机 读出噪音。拟议的项目旨在实现算法，以允许执行以下估计任务 以尽可能高的准确度对分子进行定位。 该项目的一个重要部分是基于Java的单项分析软件框架 分子实验数据。其核心将是为 分析算法将允许以简化的方式合并不同的模型 单个分子的图像配置文件，不同的相机相关数据生成过程，不同 数据的预处理步骤，以及不同的估计算法。通过使用图形处理 在这些单位中，将利用总体数据分析的大规模并行结构。 利用我们早期的信息理论成果，我们还将开发方法和支持 允许显微镜操作员分析诸如曝光时间、 激发级别、放大倍数和像素大小，并通过这样做来设计一个实验，该实验将产生 为后续分析优化的数据。这将得到分析方法的补充 物镜的质量、二向色滤光片的性能、相机的噪声水平等。 具体目标1：开发包含模块的单分子数据分析平台 用于单分子示踪和单分子超分辨显微镜，目标2：开发一种 单分子显微镜实验设计和仪器表征的框架。 该提议源于德克萨斯A&M大学的一家剥离公司，该公司寻求进一步 开发十多年来开发的单分子方法并将其商业化。

PROJECT SUMMARY/ABSTRACT Single molecule microscopy is a relatively novel technique that allows individual molecules to be imaged using the optical microscope. It is of major interest to scientists because it enables the observation of cellular processes at the molecular level, a task that is not achievable with classical optical imaging approaches due to the cellular processes being obscured by averaging and bulk effects. Single molecule tracking and localization-based superresolution microscopy (PALM/STORM) are two of the main examples of single molecule imaging experiments. The improvement of these techniques over classical imaging approaches is directly dependent on the accuracy with which the position of the single molecules in the sample can be estimated. This leads to two major challenges. One, the design of experiments such that the best possible data can be obtained. Two, the analysis of the data in the most optimal fashion. The technical difficulties of single molecule experiments are to a large extent due to the very low photon count in the presence of significant noise sources such as scattered photons and camera readout noise. The proposed project aims to implement algorithms to permit estimation tasks such as the localization of a molecule to be carried out with the best possible accuracy. An important part of the project is a Java-based software framework for the analysis of single molecule experimental data. At its core will be a carefully designed software architecture for the analysis algorithms that will allow in a streamlined fashion the incorporation of different models for the image profiles of single molecules, different camera-dependent data generation processes, different data pre-processing steps, and different estimation algorithms. By employing graphical processing units, advantage will be taken of the massively parallel structure of the overall data analysis. Exploiting our earlier information-theoretic results, we will also develop approaches and supporting software to allow the microscopist to analyze the impact of parameters such as exposure time, excitation level, magnification, and pixel size, and by doing so, design an experiment that will produce data that is optimized for the subsequent analysis. This will be complemented by methods to analyze the quality of the objective lens, the performance of dichroic filters, the noise level of cameras, etc. The specific aims are Aim 1: to develop a single molecule data analysis platform including modules for single molecule tracking and single molecule superresolution microscopy, and Aim 2: to develop a framework for experimental design and instrument characterization in single molecule microscopy. The proposal originates from a spin-out company of Texas A&M University that seeks to further develop and commercialize single molecule methodologies developed over more than a decade.