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English(EN) VOICE: A Vision-Omics Foundation Model Integrating Direct and Retrieval-Based Prediction of In-situ Single-Cell Gene Expression

新的VOICE模型可从组织图像预测基因表达

研究人员开发了VOICE,一个整合了视觉和组学数据的新型基础模型,可从H&E染色组织图像预测单细胞基因表达。该模型将细胞形态与基因表达嵌入对齐,利用了直接回归和基于检索的预测分支。VOICE展示了强大的泛化能力,在跨越未见过患者和切片的七项指标上均优于先前的方法。 AI

影响 该模型通过对易于获得的组织图像进行大规模基因表达分析,有望显著推动生物学研究。

排序理由 该集群包含一篇详细介绍用于生物数据分析的新基础模型的研究论文。

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的VOICE模型可从组织图像预测基因表达

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该集群包含一篇详细介绍用于生物数据分析的新基础模型的研究论文。
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xin Luo, Yicheng Tao, Haoxuan Zeng, Suyuan Wang, Chenzi Ouyang, Meiqi Zhu, Kai Liu, Shuibing Chen, Jie Liu ·

    VOICE:一种整合了直接和检索式预测原位单细胞基因表达的视觉组学基础模型

    arXiv:2608.08366v1 Announce Type: new Abstract: Spatial transcriptomics can resolve gene expression at single-cell resolution, but it is costly, limited to targeted panels of a few hundred to a few thousand genes, and applicable to only a small number of samples. H&amp;E imaging,…