用超图小波表示细胞空间关系，发现阿尔茨海默病关键微环境。
Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics
- 用超图扩散小波捕捉多细胞复杂交互关系。
- 在阿尔茨海默病数据中识别出疾病相关细胞微环境。
- 适合生物医学图像分析与空间转录组研究者。
在众多数据驱动应用中，多个对象间的高阶关系对刻画复杂交互至关重要。超图通过允许多个节点连接于同一条边，为建模此类高阶关系提供了灵活而强大的框架。本文提出超图扩散小波，并描述其优良的谱特性和空间特性。通过将该方法应用于空间分辨转录组学，展示了其在生物医学发现中的实用性，成功表征了阿尔茨海默病相关的细胞微环境。
原文摘要 · Abstract (English)
In many data-driven applications, higher-order relationships among multiple objects are essential in capturing complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect any number of nodes, provide a flexible and powerful framework for modeling such higher-order relationships. In this work, we introduce hypergraph diffusion wavelets and describe their favorable spectral and spatial properties. We demonstrate their utility for biomedical discovery in spatially resolved transcriptomics by applying the method to represent disease-relevant cellular niches for Alzheimer's disease.
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