MassVision:一个开源端到端的平台,用于人工智能驱动的质谱成像分析
Amoon Jamzad1, Jade Warren1, Ayesha Syeda1
1School of Computing, Queen's University, Kingston, Ontario K7L 2N8, Canada.
Analytical chemistry
|September 18, 2025
概括
MassVision是一个新的软件平台,简化了复杂的质谱成像 (MSI) 数据分析. 它为研究人员提供了一个集成的,用户友好的解决方案,从MSI数据中获得更深入的生物学见解.
科学领域:
- 生物医学成像学 生物医学成像学
- 计算生物学是一种计算生物学.
- 数据科学是数据科学.
背景情况:
- 质谱成像 (MSI) 产生了丰富的空间和光谱数据用于分子分析.
- MSI数据分析是计算密集型的,需要编码专业知识和经常碎片化的工作流.
- 目前的工具缺乏整合,阻碍了研究人员的效率和可访问性.
研究的目的:
- 介绍MassVision,这是一个全面和用户友好的软件平台,用于质谱成像数据分析.
- 解决MSI数据分析中的计算和可访问性挑战.
- 为端到端的MSI工作流提供综合解决方案.
主要方法:
- MassVision 是建立在 3D Slicer 生态系统上,提供了一个直观的界面.
- 关键功能包括可视化,细分,协同定位,数据合并,预处理,统计分析和AI模型部署.
- 该平台支持高通量研究和多幻灯片数据集.
主要成果:
- 在探索性数据分析,离子识别和组织类型分类方面,MassVision表现出有效性.
- 该平台无集成各种MSI数据处理步骤.
- 案例研究使用了来自不同模式的内部和公共MSI数据.
结论:
- 在MSI分析中,MassVision降低了研究人员在MSI分析中不同计算专业知识的障碍.
- 该平台有助于从MSI数据中发现新的生物见解和结构.
- MassVision提供了一个强大的,集成的工具,用于推进MSI数据分析和解释.
相关概念视频
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01:16Mass Spectrometers
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01:13Mass Analyzers: Overview
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01:23Mass Spectrum
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01:08Matrix-Assisted Laser Desorption Ionization (MALDI)
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