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English(EN) COAST: Context-Aware Differential Learning for Gene Expression Prediction in Spatial Transcriptomics

新的COAST框架增强了空间转录组学中的基因表达预测

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了COAST，一种利用组织学图像预测空间转录组学中基因表达的新框架。这种上下文感知的差异学习方法利用局部和全局上下文特征，并结合Transformer编码器来捕捉复杂的模式。COAST使用目标点和上下文点之间的绝对表达回归以及有符号差异回归的组合目标进行训练，在多个数据集上表现出改进的性能。 AI

影响 该框架有望提高生物学研究中基因表达分析的准确性和效率。

排序理由 该集群包含一篇详细介绍特定科学领域新机器学习框架的学术论文。

在 arXiv cs.LG 阅读 →

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新的COAST框架增强了空间转录组学中的基因表达预测

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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Keunho Byeon, Sunhong Park, Jeewoo Lim, Jin Tae Kwak ·

    COAST：基因表达空间转录组学预测的上下文感知差分学习

    arXiv:2607.09166v1 Announce Type: new Abstract: Spatial transcriptomics enables profiling of spatial gene expression but is limited by high cost and low throughput, motivating prediction from H&amp;E histopathology images. Existing context-aware methods mainly supervise absolute …

  2. arXiv cs.LG TIER_1 English(EN) · Jin Tae Kwak ·

    COAST：基因表达空间转录组学预测的上下文感知差分学习

    Spatial transcriptomics enables profiling of spatial gene expression but is limited by high cost and low throughput, motivating prediction from H&E histopathology images. Existing context-aware methods mainly supervise absolute expression, while relative expression relationships …

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