MSIpixel:在质谱成像实验中用于化合物注释和量化的全自动管道
Lavinia Morosi1, Matteo Miotto1, Sara Timo1
1IRCCS Humanitas Research Hospital, Via Manzoni 56, Rozzano (MI), Italy.
Briefings in bioinformatics
|December 15, 2023
概括
本研究介绍了MSIpixel,这是一个用于质谱成像 (MSI) 的自动化管道,可以增强空间代谢学中的分子识别和代谢物注释. 这种方法提高了MSI数据分析的可靠性和全面性.
科学领域:
- 生物医学科学 生物医学科学
- 分析化学 分析化学
- 代谢学 代谢学 代谢学
背景情况:
- 质谱成像 (MSI) 对于绘制生物样本中小分子分布的地图至关重要.
- 在基于MSI的空间代谢学中,分子识别和代谢物注释仍然是重大挑战.
- 目前的方法通常依赖于并行批量LC-MS2分析进行验证.
研究的目的:
- 在MSI实验中直接开发一个用于化合物注释和量化的自动化管道.
- 解决分子识别的局限性,提高MSI数据的可靠性.
- 为了使在单个仪器运行中可视化和识别未知的分子.
主要方法:
- 应用一种使用数据依赖采集的质谱成像 (MSI) 方法.
- 开发和实施MSIpixel,一个完全自动化的计算管道.
- 在MSI工作流程中整合注释和量化功能.
主要成果:
- 使用MSI成功可视化和识别未知分子.
- 展示MSIpixel在自动复合注释和量化方面的能力.
- 克服分子识别方面的挑战,以加强MSI数据分析.
结论:
- MSIpixel显著提高了基于MSI的空间代谢学的可靠性和全面性.
- 自动化管道促进了更强大的分子识别和代谢物注释.
- 这种方法提升了MSI对复杂生物矩阵分析的实用性.
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