Paper Citation Record · LEDGER

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images

As of 17 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.02601.

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2412.02601 v2

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Outbound references

Observation 64fc0e29-d7e9-42e4-84f4-589822b8a29a · outbound

This paper cites Principal component analysis.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Principal component analysis

Reference 1

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This paper cites Goodwin, Anubhav Sinha, et al.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Goodwin, Anubhav Sinha, et al

Reference 2

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This paper cites Spatial deconvolution of her2-positive breast tumors reveals novel intercellular relationships.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Spatial deconvolution of her2-positive breast tumors reveals novel intercellular relationships

Reference 3

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This paper cites Layer Normalization.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Layer Normalization

Reference 4

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This paper cites Boettiger, Jeffrey R.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Boettiger, Jeffrey R

Reference 5

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This paper cites Towards a general-purpose foundation model for computational pathol- ogy.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Towards a general-purpose foundation model for computational pathol- ogy

Reference 6

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This paper cites Accurate spatial gene expression prediction by integrating multi-resolution features.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Accurate spatial gene expression prediction by integrating multi-resolution features

Reference 7

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This paper cites Borm, Amit Zeisel, et al.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Borm, Amit Zeisel, et al

Reference 8

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This paper cites Sys- tematic comparison of single-cell and single-nucleus rna- sequencing methods.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Sys- tematic comparison of single-cell and single-nucleus rna- sequencing methods

Reference 9

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

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This paper cites Transcriptome-scale super-resolved imaging in tissues by rna seqfish+.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Transcriptome-scale super-resolved imaging in tissues by rna seqfish+

Reference 11

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This paper cites Inductive representation learning on large graphs.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Inductive representation learning on large graphs

Reference 12

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This paper cites In- tegrating spatial gene expression and breast tumour morphol- ogy via deep learning.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images In- tegrating spatial gene expression and breast tumour morphol- ogy via deep learning

Reference 13

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This paper cites Deep residual learning for image recognition.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Deep residual learning for image recognition

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This paper cites A systematic evaluation of single-cell rna-sequencing imputation methods.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images A systematic evaluation of single-cell rna-sequencing imputation methods

Reference 15

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This paper cites Densely connected convolutional net- works.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Densely connected convolutional net- works

Reference 16

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This paper cites Saver: gene expression recovery for single-cell rna sequencing.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Saver: gene expression recovery for single-cell rna sequencing

Reference 17

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This paper cites A visual–language foundation model for pathology image anal- ysis using medical twitter.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images A visual–language foundation model for pathology image anal- ysis using medical twitter

Reference 18

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This paper cites Mrna stability and overexpression of fatty acid synthase in human breast cancer cell lines.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Mrna stability and overexpression of fatty acid synthase in human breast cancer cell lines

Reference 19

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This paper cites HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis

Reference 20

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This paper cites Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma

Reference 21

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This paper cites Thitogene: a deep learning method for predicting spatial transcriptomics from histological images.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Thitogene: a deep learning method for predicting spatial transcriptomics from histological images

Reference 22

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This paper cites Elevated expression of gnas pro- motes breast cancer cell proliferation and migration via the pi3k/akt/snail1/e-cadherin axis.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Elevated expression of gnas pro- motes breast cancer cell proliferation and migration via the pi3k/akt/snail1/e-cadherin axis

Reference 23

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This paper cites Bayesian approach to single-cell differential expression anal- ysis.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Bayesian approach to single-cell differential expression anal- ysis

Reference 24

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This paper cites Fast, sen- sitive and accurate integration of single-cell data with har- mony.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Fast, sen- sitive and accurate integration of single-cell data with har- mony

Reference 25

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This paper cites SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression

Reference 26

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This paper cites Visual language pretrained multiple instance zero-shot transfer for histopathology images.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Visual language pretrained multiple instance zero-shot transfer for histopathology images

Reference 27

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This paper cites A visual-language foundation model for computational pathol- ogy.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images A visual-language foundation model for computational pathol- ogy

Reference 28

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This paper cites EAGS: efficient and adaptive Gaussian smoothing applied to high-resolved spatial transcriptomics.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images EAGS: efficient and adaptive Gaussian smoothing applied to high-resolved spatial transcriptomics

Reference 29

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Observation 84fb01c5-b4a7-4f63-b3cd-610a9efd6e5d · outbound

This paper cites Leverag- ing information in spatial transcriptomics to predict super- resolution gene expression from histology images in tumors.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Leverag- ing information in spatial transcriptomics to predict super- resolution gene expression from histology images in tumors

Reference 30

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This paper cites St ˚ahl, Fredrik Salm ´en, Sanja Vickovic, et al.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images St ˚ahl, Fredrik Salm ´en, Sanja Vickovic, et al

Reference 31

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This paper cites Patches Are All You Need?.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Patches Are All You Need?

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This paper cites Re- covering gene interactions from single-cell data using data diffusion.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Re- covering gene interactions from single-cell data using data diffusion

Reference 33

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This paper cites Attention is all you need.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Attention is all you need

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MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Graph Attention Networks

Reference 35

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This paper cites High-definition spatial transcriptomics for in situ tissue pro- filing.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images High-definition spatial transcriptomics for in situ tissue pro- filing

Reference 36

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This paper cites A foundation model for clinical-grade computational pathol- ogy and rare cancers detection.Nature medicine, pages 1–12,.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images A foundation model for clinical-grade computational pathol- ogy and rare cancers detection.Nature medicine, pages 1–12,

Reference 37

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This paper cites Allen, Matthew A.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Allen, Matthew A

Reference 38

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Observation 1b3d816d-e40a-4c89-ad89-d261807bcab2 · outbound

This paper cites Spatially re- solved gene expression prediction from histology images via bi-modal contrastive learning.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Spatially re- solved gene expression prediction from histology images via bi-modal contrastive learning

Reference 39

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Observation 9d1158c8-2e11-4653-8eda-2cf8705a7148 · outbound

This paper cites Exemplar guided deep neural network for spatial tran- scriptomics analysis of gene expression prediction.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Exemplar guided deep neural network for spatial tran- scriptomics analysis of gene expression prediction

Reference 40

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Observation ee4d8abd-a948-47b7-a477-939406b3a798 · outbound

This paper cites Spatial tran- scriptomics prediction from histology jointly through Trans- former and graph neural networks.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Spatial tran- scriptomics prediction from histology jointly through Trans- former and graph neural networks

Reference 41

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This paper cites Experimental Setup The ResNet18-based patch encoder is implemented in Py- Torch (version 2.2.2).

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Experimental Setup The ResNet18-based patch encoder is implemented in Py- Torch (version 2.2.2)

Reference 42

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This paper cites Results Comparison - PCC This section discusses the PCC scores attained by MERGE and TRIPLEX across the samples in ST-Net dataset for two cancer-relevant genes - FASN and GNAS.

MERGE: Multi-faceted Hierarchical Graph-based GNN for Gene Expression Prediction from Whole Slide Histopathology Images Results Comparison - PCC This section discusses the PCC scores attained by MERGE and TRIPLEX across the samples in ST-Net dataset for two cancer-relevant genes - FASN and GNAS

Reference 43

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