Spatial Transcriptomics Integration with Deep Learning Models

Ai Cancer Biology › Spatial Transcriptomics AI in Cancer Research

Spatial Transcriptomics Integration with Deep Learning Models

This research investigates how convolutional neural networks and graph neural networks can process spatial transcriptomic data to identify novel gene expression patterns in tumor microenvironments. The work advances understanding of how machine learning architectures can capture both local and global spatial dependencies to reveal previously undetected cell-cell communication networks in cancer tissues.

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