mViSE:用于分析多重IHC脑组织图像 (空间蛋白质组学) 的视觉搜索引擎
Liqiang Huang1, Rachel Mills1, Saikiran Mandula1
1University of Houston, Houston, TX, 77204, USA.
Scientific reports
|February 22, 2026
概括
我们开发了mVISE,这是一款用于分析大规模空间蛋白质组学大脑图像的视觉搜索引擎. 这个工具可以实现无编程,查询驱动的检索和细胞社区和组织的概况.
科学领域:
- 神经科学是一个神经科学.
- 计算生物学 计算生物学
- 生物技术是生物技术.
背景情况:
- 脑组织的全幻灯片空间蛋白质组图像很大,很复杂,这给分析带来了挑战.
- 当前的方法往往需要编程专业知识或缺乏全面的分析能力.
研究的目的:
- 介绍mVISE,一种交互式视觉搜索引擎,用于对多重空间蛋白质组学数据的无编程分析.
- 为了实现基于查询驱动的检索和细胞社区和大脑组织内的多细胞的概况.
主要方法:
- 开发了在细胞形态学,化学架构,细胞架构和骨髓架构上训练的多重编码器,没有人类注释.
- 在成像通道中集成视觉线索,以克服基础模型的局限性.
- 结合多个编码器用于专门的搜索功能.
主要成果:
- 经过验证的mVISE用于检索单细胞,细胞对和组织贴片.
- 证明了皮层层,大脑区域和子区域的准确划分.
- 展示了复杂的空间蛋白质组学数据的无编程,查询驱动的分析.
结论:
- mVISE为分析庞大的空间蛋白质组学数据集提供了一种有效,可访问的替代方案.
- 该工具有助于探索性分析,比较分析和大脑结构的划分.
- mVISE可以作为一个开源的QuPath插件,促进在神经科学研究中更广泛的采用.
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