Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data | Paper Citation Record

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Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Unresolved cited work

Reference 1

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This paper cites gold standard.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data gold standard

Reference 2

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This paper cites NicheNet: modeling intercellular communication by linking ligands to target genes,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data NicheNet: modeling intercellular communication by linking ligands to target genes,

Reference 3

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This paper cites training set.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data training set

Reference 4

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This paper cites Cell –cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Cell –cell communication inference and analysis in the tumour microenvironments from single-cell transcriptomics: data resources and computational strategies,

Reference 5

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This paper cites Transcriptome analysis of individual stromal cell populations identifies stroma-tumor crosstalk in mouse lung cancer model,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Transcriptome analysis of individual stromal cell populations identifies stroma-tumor crosstalk in mouse lung cancer model,

Reference 6

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This paper cites Immune landscape of viral -and carcinogen-driven head and neck cancer,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Immune landscape of viral -and carcinogen-driven head and neck cancer,

Reference 7

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This paper cites PyMINEr finds gene and autocrine-paracrine networks from human islet scRNA-Seq,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data PyMINEr finds gene and autocrine-paracrine networks from human islet scRNA-Seq,

Reference 8

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This paper cites Cell lineage and communication network inference via optimization for single -cell transcriptomics,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Cell lineage and communication network inference via optimization for single -cell transcriptomics,

Reference 9

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This paper cites SingleCellSignalR: inference of intercellular networks from single -cell transcriptomics,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data SingleCellSignalR: inference of intercellular networks from single -cell transcriptomics,

Reference 10

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This paper cites Comprehensive integration of single -cell data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Comprehensive integration of single -cell data,

Reference 11

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This paper cites Inferring spatial and signaling relationships between cells from single cell transcriptomic data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Inferring spatial and signaling relationships between cells from single cell transcriptomic data,

Reference 12

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This paper cites histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data,

Reference 13

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This paper cites scPriorGraph: constructing biosemantic cell–cell graphs with prior gene set selection for cell type identification from scRNA-seq data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scPriorGraph: constructing biosemantic cell–cell graphs with prior gene set selection for cell type identification from scRNA-seq data,

Reference 14

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This paper cites scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scGCN is a graph convolutional networks algorithm for knowledge transfer in single cell omics,

Reference 15

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This paper cites Reference -based analysis of lung single -cell sequencing reveals a transitional profibrotic macrophage,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Reference -based analysis of lung single -cell sequencing reveals a transitional profibrotic macrophage,

Reference 16

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This paper cites Despite the differing methodologies in constructing graphs, these approaches have confirmed that establishing links between cells is beneficial for predicting cell types.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Despite the differing methodologies in constructing graphs, these approaches have confirmed that establishing links between cells is beneficial for predicting cell types

Reference 17

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This paper cites Probabilistic cell -type assignment of single -cell RNA -seq for tumor microenvironment profiling,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Probabilistic cell -type assignment of single -cell RNA -seq for tumor microenvironment profiling,

Reference 18

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This paper cites scCATCH: automatic annotation on cell types of clusters from single-cell RNA sequencing data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scCATCH: automatic annotation on cell types of clusters from single-cell RNA sequencing data,

Reference 19

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This paper cites Inference and analysis of cell -cell communication using CellChat,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Inference and analysis of cell -cell communication using CellChat,

Reference 20

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This paper cites scPML: pathway-based multi-view learning for cell type annotation from single-cell RNA-seq data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scPML: pathway-based multi-view learning for cell type annotation from single-cell RNA-seq data,

Reference 21

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This paper cites SCENIC: single -cell regulatory network inference and clustering,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data SCENIC: single -cell regulatory network inference and clustering,

Reference 22

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This paper cites KEGG: kyoto encyclopedia of genes and genomes,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data KEGG: kyoto encyclopedia of genes and genomes,

Reference 23

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This paper cites C/EBPα and GATA-2 mutations induce bilineage acute erythroid leukemia through transformation of a neomorphic neutrophil -erythroid progenitor,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data C/EBPα and GATA-2 mutations induce bilineage acute erythroid leukemia through transformation of a neomorphic neutrophil -erythroid progenitor,

Reference 24

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This paper cites Single-cell analysis of childhood leukemia reveals a link between developmental states and ribosomal protein expression as a source of intra -individual heterogeneity,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Single-cell analysis of childhood leukemia reveals a link between developmental states and ribosomal protein expression as a source of intra -individual heterogeneity,

Reference 25

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This paper cites Risk-associated alterations in marrow T cells in pediatric leukemia,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Risk-associated alterations in marrow T cells in pediatric leukemia,

Reference 26

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This paper cites A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling,

Reference 27

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This paper cites Cancer cells deploy lipocalin-2 to collect limiting iron in leptomeningeal metastasis,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Cancer cells deploy lipocalin-2 to collect limiting iron in leptomeningeal metastasis,

Reference 28

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This paper cites Pairwise Alignment Improves Graph Domain Adaptation.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Pairwise Alignment Improves Graph Domain Adaptation

Reference 29

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This paper cites Exact matrix completion via convex optimization,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Exact matrix completion via convex optimization,

Reference 30

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This paper cites MarkerCount: A stable, count-based cell type identifier for single -cell RNA -seq experiments,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data MarkerCount: A stable, count-based cell type identifier for single -cell RNA -seq experiments,

Reference 31

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This paper cites CHETAH: a selective, hierarchical cell type identification method for single -cell RNA sequencing,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data CHETAH: a selective, hierarchical cell type identification method for single -cell RNA sequencing,

Reference 32

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This paper cites SingleCellNet: a computational tool to classify single cell RNA- Seq data across platforms and across species,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data SingleCellNet: a computational tool to classify single cell RNA- Seq data across platforms and across species,

Reference 33

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This paper cites Learning for single-cell assignment,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Learning for single-cell assignment,

Reference 34

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This paper cites scPred: accurate supervised method for cell-type classification from single-cell RNA-seq data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scPred: accurate supervised method for cell-type classification from single-cell RNA-seq data,

Reference 35

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This paper cites scmap: projection of single -cell RNA-seq data across data sets,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scmap: projection of single -cell RNA-seq data across data sets,

Reference 36

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This paper cites SciBet as a portable and fast single cell type identifier,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data SciBet as a portable and fast single cell type identifier,

Reference 37

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This paper cites scClassify: sample size estimation and multiscale classification of cells using single and multiple reference,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data scClassify: sample size estimation and multiscale classification of cells using single and multiple reference,

Reference 38

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This paper cites The reactome pathway knowledgebase 2022,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data The reactome pathway knowledgebase 2022,

Reference 39

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This paper cites WikiPathways: connecting communities,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data WikiPathways: connecting communities,

Reference 40

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This paper cites Pathway Commons, a web resource for biological pathway data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Pathway Commons, a web resource for biological pathway data,

Reference 41

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This paper cites CancerSEA: a cancer single-cell state atlas,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data CancerSEA: a cancer single-cell state atlas,

Reference 42

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This paper cites GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:49:54.930335Z

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This paper cites Recruitment of Sprouty1 to immune synapse regulates T cell receptor signaling,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Recruitment of Sprouty1 to immune synapse regulates T cell receptor signaling,

Reference 44

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This paper cites Association of CD147 and calcium exporter PMCA4 uncouples IL- 2 expression from early TCR signaling,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Association of CD147 and calcium exporter PMCA4 uncouples IL- 2 expression from early TCR signaling,

Reference 45

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This paper cites Nifetepimine, a dihydropyrimidone, ensures CD4+ T cell survival in a tumor microenvironment by maneuvering sarco (endo) plasmic reticulum Ca2+ ATPase (SERCA),.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Nifetepimine, a dihydropyrimidone, ensures CD4+ T cell survival in a tumor microenvironment by maneuvering sarco (endo) plasmic reticulum Ca2+ ATPase (SERCA),

Reference 46

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This paper cites Zap70 controls the interaction of talin with integrin to regulate the chemotactic directionality of T -cell migration,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Zap70 controls the interaction of talin with integrin to regulate the chemotactic directionality of T -cell migration,

Reference 47

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This paper cites Survivin-3B potentiates immune escape in cancer but also inhibits the toxicity of cancer chemotherapy,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Survivin-3B potentiates immune escape in cancer but also inhibits the toxicity of cancer chemotherapy,

Reference 48

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Observation ad4e8beb-1688-4cbb-90fc-e688276fe471 · outbound

This paper cites Downregulation of SIRT7 by 5 -fluorouracil induces radiosensitivity in human colorectal cancer,.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Downregulation of SIRT7 by 5 -fluorouracil induces radiosensitivity in human colorectal cancer,

Reference 49

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This paper cites Proximal splitting methods in signal processing.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data Proximal splitting methods in signal processing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:49:54.831235Z

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Observation 1c77bbe7-bdbb-4088-83dc-386719344b47 · outbound

This paper cites A generalized forward-backward splitting.

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data A generalized forward-backward splitting

Reference 51

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