Spatially resolved prediction of drug sensitivity in the tumor microenvironment via deep graph contrastive and transfer learning
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Updated
Jul 26, 2026 - Jupyter Notebook
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spatial-transcriptome
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R scripts for preprocessing, pathway scoring, Bayesian modeling, and Cox proportional hazards analyses applied to the SCAPeSCLC dataset, integrating GeoMx Cancer Transcriptome Atlas expression and survival outcomes in ES-SCLC patients treated with chemo-immunotherapy.
bioinformatics bioinformatics-pipeline survival-analysis lung-cancer bayesian-inference transcriptomics bayesian-statistics oncology-data lung-cancer-classification spatial-transcriptomics transcriptomics-datasets transcriptomics-data-integration transcriptomics-data cancer-transcriptome-profiles lung-cancer-survivability proportional-hazards lung-cancer-data-set cancer-transcriptomics spatial-transcriptome spatial-transcriptomics-analyses
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Updated
Aug 8, 2026 - R
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