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高分辨率成像质谱中大型图像数据集可视化的工具与策略

Tools and strategies for visualization of large image data sets in high-resolution imaging mass spectrometry.

作者信息

Klinkert Ivo, McDonnell Liam A, Luxembourg Stefan L, Altelaar A F Maarten, Amstalden Erika R, Piersma Sander R, Heeren Ron M A

机构信息

FOM Institute for Atomic and Molecular Physics FOM-AMOLF, Kruislaan 407, 1098 SJ Amsterdam, The Netherlands.

出版信息

Rev Sci Instrum. 2007 May;78(5):053716. doi: 10.1063/1.2737770.

Abstract

Mass spectrometry based proteomics is one of the scientific domains in which experiments produce a large amount of data that need special environments to interpret the results. Without the use of suitable tools and strategies, the transformation of the large data sets into information is not easily achievable. Therefore, in the context of the virtual laboratory of enhanced science, software tools are developed to handle mass spectrometry data sets. Using different data processing strategies for visualization, it enables fast mass spectrometric imaging of large surfaces at high-spatial resolution and thus aids in the understanding of various diseases and disorders. This article describes how to optimize the handling and processing of the data sets, including the selection of the most optimal data formats and the use of parallel processing. It also describes the tools and solutions and their application in mass spectrometric imaging strategies, including new measurement principles, image enhancement, and image artifact suppression.

摘要

基于质谱的蛋白质组学是一个科学领域,在该领域中实验会产生大量数据,需要特殊环境来解释结果。如果不使用合适的工具和策略,将大量数据集转化为信息并非易事。因此,在增强科学的虚拟实验室背景下,开发了软件工具来处理质谱数据集。通过使用不同的数据处理策略进行可视化,它能够以高空间分辨率对大表面进行快速质谱成像,从而有助于理解各种疾病和紊乱。本文描述了如何优化数据集的处理和加工,包括选择最优数据格式以及使用并行处理。它还描述了工具和解决方案及其在质谱成像策略中的应用,包括新的测量原理、图像增强和图像伪影抑制。

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