Functional enrichment analysis of the 28 DNB genes identified for ESCC. 由 Fatemeh Keikha (20917848)

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Quantitative performance comparison of our method and five multilayer network ranking baselines on the GAC dataset across multiple evaluation metrics. 由 Fatemeh Keikha (20917848)

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Simulation networks and gene expression analysis across disease states. 由 Fatemeh Keikha (20917848)

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UpSet diagram illustrating the overlap of DNBs selected by our method and top-ranked genes by the 13 baseline centrality-based ranking algorithms. 由 Fatemeh Keikha (20917848)

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Mean expression levels of biomarker genes across various disease states. 由 Fatemeh Keikha (20917848)

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Overview of the TransMarker framework for identifying DNBs from single cell time course data. 由 Fatemeh Keikha (20917848)

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UMAP visualizations of extracted CD8⁺ T and CD4⁺ T cell barcodes, employed for downstream subsequent single-cell trajectory and classification analyses.... 由 Fatemeh Keikha (20917848)

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Comparison of Gene Discovery and Performance Evaluation with Baseline Methods. 由 Fatemeh Keikha (20917848)

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Ablation studies and performance evaluation under varying training conditions. 由 Fatemeh Keikha (20917848)

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Robustness of TransMarker concerning the selection and completeness of the prior knowledge network. 由 Fatemeh Keikha (20917848)

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Case study on Esophageal Squamous Cell Carcinoma (ESCC). 由 Fatemeh Keikha (20917848)

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Functional enrichment analysis of the DNBs identified for GAC. 由 Fatemeh Keikha (20917848)

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Gene regulatory networks for different states of GAC post-rewiring. 由 Fatemeh Keikha (20917848)

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Classification performance across the three simulation settings. 由 Fatemeh Keikha (20917848)

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Robustness analysis of the entropic regularization parameter in the Gromov–Wasserstein alignment step of TransMarker. 由 Fatemeh Keikha (20917848)

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classification results on simulated datasets and biomarkers and classification results for GAC dataset. 由 Fatemeh Keikha (20917848)

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