Support and Development of EMAN for Electron Microscopy Image Processing

EMAN 对电子显微镜图像处理的支持和开发

• 批准号: 7912125
• 负责人: STEVEN J LUDTKE
• 金额: $ 19.81万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-11 至 2011-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7912125
• 关键词: Adopted; Algorithms; Archives; Automation; Basic Science; Biological; Cell physiology; Cells; Charge; Code; Complex; Computer software; Cryoelectron Microscopy; Data; Dependency; Development; Diagnosis; Dimensions; Documentation; Electron Microscopy; Environment; Flavoring; Goals; Health Benefit; Hour; Image; Imagery; Individual; Libraries; Life; Linux; Methods; Microscopy; Modeling; Molecular; Molecular Chaperones; Muscle function; Procedures; Process; Public Health; Published Comment; Pythons; Request for Proposals; Research; Research Infrastructure; Research Personnel; Resolution; Resources; Ribosomes; Running; Scientist; Source; Structure; System; Techniques; Testing; Time; Transmission Electron Microscopy; Update; Virus; Virus Diseases; Work; base; design; direct application; electron tomography; flexibility; image processing; improved; interest; molecular assembly/self assembly; nanometer; open source; particle; pathogen; programs; reconstruction; tool; wiki

DESCRIPTION (provided by applicant): EMAN is a software suite for two and three dimensional image processing of transmission electron microscopy data. Its original design was specifically to perform the compuations required for a technique known as single particle reconstruction. This technique allows the structure of molecules and molecular assemblies in the 10 to 1,000 nanometer range to be fully determined in three dimensions. The molecules and assemblies studied cover the full range of cellular processes. Systems studied using this technique are far too diverse to adequately describe, but some examples include: GroEL, a molecular chaperone, the ribosome, one of the most fundamental assemblies found in all living cells and Ca++ release channel, a critical component in muscle function. This technique has also been crucial in the determination of virus structures, which aid in understanding their function and hence design of new treatments and diagnoses for viral diseases. The computation required to perform these reconstructions is considerable, generally requiring tens to hundreds of thousands of CPU-hours on modern PC clusters to complete. EMAN was designed to automate the reconstruction process to the greatest extent possible to allow higher resolution structures to be obtained, and for the processing to occur more quickly and accurately than previously possible. Since its initial release, the core library has also been used in projects relating to x-ray crystallograpy, electron tomography, structure analysis tools, and molecular visualization. It has also begun to find some use in other high resolution microscopies, such as AFM and image processing of non-biological TEM images. In this proposal we request support to continue to develop and support this package for the benefit of its many hundreds of users worldwide. This will include redeisgn of the core library to make it easier to use by basic scientists through use of an improved Python interface, improvements to documentation and user support, and better cross-platform support. The work this software supports is generally considered basic science, with public health benefits coming from a better understanding of the fundamental processes within the cell. More direct applications of this technique also exist. As one example, for bioterror defence, this technique has been proposed for rapid determination of the structure of an unknown pathogen, allowing rapid identification and distribution of the correct countermeasures.

描述（由申请人提供）：EMAN是用于透射电子显微镜数据的二维和三维图像处理的软件套件。它最初的设计是专门用于执行被称为单粒子重建的技术所需的计算。该技术允许在10至1，000纳米范围内完全确定分子和分子组装体的三维结构。所研究的分子和组装体涵盖了细胞过程的全部范围。使用这种技术研究的系统过于多样化，无法充分描述，但一些例子包括：GroEL，分子伴侣，核糖体，在所有活细胞中发现的最基本的组件之一，以及Ca++释放通道，肌肉功能的关键组成部分。这项技术在确定病毒结构方面也至关重要，这有助于了解它们的功能，从而设计新的治疗方法和诊断病毒性疾病。执行这些重建所需的计算是相当大的，通常需要在现代PC集群上完成数万到数十万个CPU小时。EMAN旨在最大程度地自动化重建过程，以获得更高分辨率的结构，并使处理比以前更快，更准确。自其首次发布以来，核心库也已被用于与X射线晶体学，电子断层扫描，结构分析工具和分子可视化相关的项目。它也开始在其他高分辨率显微镜中找到一些用途，例如AFM和非生物TEM图像的图像处理。在本提案中，我们请求支持继续开发和支持这一软件包，以造福于全球数百名用户。这将包括重新设计核心库，通过使用改进的Python界面，改进文档和用户支持以及更好的跨平台支持，使基础科学家更容易使用。该软件支持的工作通常被认为是基础科学，公共卫生的好处来自于更好地了解细胞内的基本过程。这种技术也有更直接的应用。例如，在生物恐怖防御方面，有人提出利用这种技术快速确定未知病原体的结构，从而能够迅速查明和分发正确的对策。