Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:42.035687Z
Paper Citation Record · LEDGER
As of 20 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2506.11491.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:42.035687Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
68 of 68 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a73a80fa-4729-4e07-a1b1-1d3f4d6346bd · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics An introduction to spatial transcriptomics for biomedical research
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Holt and Simon L
Reference 2
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Single-cell in situ rna profiling by sequential hybridization
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex
Reference 4
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Observation 8c32a79e-0b65-4125-92b3-e1def4b892db · outbound
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Three-dimensional intact-tissue se- quencing of single-cell transcriptional states
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Transcriptome-scale super-resolved imaging in tissues by rna seqfish+
Reference 7
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Visualization and analysis of gene expression in tissue sections by spatial transcriptomics
Reference 8
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Observation 58eff9b9-f0cd-4aef-8452-ffa19467f3f4 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Highly sensitive spatial transcriptomics at near-cellular resolution with slide-seqv2
Reference 9
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics High- definition spatial transcriptomics for in situ tissue profiling
Reference 10
Source-reported events for the cited work
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Observation 0fc307f3-daa3-4466-81ed-cadd94ba5376 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Laser-capture microdissection
Reference 11
Source-reported events for the cited work
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Observation 24141a28-1963-4d77-87dc-315b389ed0c9 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Spatial recon- struction of single-cell gene expression data
Reference 12
Source-reported events for the cited work
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Observation 22496180-fe7d-4782-a9f4-f32856d5e8d1 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Giotto: a toolbox for integrative analysis and visualization of spatial expression data
Reference 13
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Observation 03f6497e-ca66-47db-8dbd-06291efc60f0 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Spagcn: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
Reference 14
Source-reported events for the cited work
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Observation 99f39ac1-1aa6-4373-8a7e-66d8e8ef28fc · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Deepst: identifying spatial domains in spatial transcriptomics by deep learning
Reference 15
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Observation 5f29b65c-5d50-4518-83a6-6a7234e1b565 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder
Reference 16
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Observation adbd0367-3384-469e-bb0a-4c329a06baad · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Unsupervised spatially embedded deep representation of spatial transcriptomics
Reference 17
Source-reported events for the cited work
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Observation 7ccd5671-eb51-49ee-aabb-c62cbf1331af · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues
Reference 18
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Observation 89366aee-e37a-495c-8d16-421ae0588f3a · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Spatially informed clustering, integra- tion, and deconvolution of spatial transcriptomics with graphst
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Source-reported events for the cited work
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Observation 5b060797-8885-4d2f-a170-a60e36d134ed · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics const: an interpretable multi-modal contrastive learning framework for spatial transcriptomics
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Observation 94d4df45-35be-4ddb-a263-2d68dcf4ea73 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Deep graph infomax
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Observation e984ad4f-a4bb-48f5-8872-1af637ff5da3 · outbound
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Reference 22
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Observation f539884a-c61d-4632-8e4f-bbbe8362d12d · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics nearest neighbor
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Observation cdfdc974-81bf-426d-8e2f-9711a23d20c7 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Museum of spatial transcriptomics
Reference 24
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Observation 3b34e537-8429-4f6d-8dcb-a1f8d89c8ac8 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Computational methods for alignment and integration of spatially resolved transcriptomics data
Reference 25
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Observation de3995aa-0b02-4ba5-ac5f-d8d744dbeae4 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Computational principles and challenges in single-cell data integration
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Observation 3bfad964-8983-4fad-b9a7-344e8daef931 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Fast, sensitive and accurate integration of single-cell data with harmony
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Observation 2a8aaff8-7acd-41a7-aa9a-a73fe254479c · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Deep generative modeling for single-cell transcriptomics
Reference 28
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Observation c860f385-e587-44b4-9ac7-b8b130b2d0c9 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Deep mincut: Learning node embeddings by detecting communities
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Observation fc78f9ec-5188-4da0-b057-292151e6b756 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Review of brain functioning in depression for semantic processing and verbal fluency
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Observation 94bcc254-6eda-4f9a-abe5-f8e5061733e7 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism
Reference 31
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Observation b8b980e7-5c5b-48ca-a850-90ff42c86852 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection
Reference 32
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Observation 071743ad-49fb-4877-bb66-8fd5e2580663 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Genome-wide association study identifies 30 loci associated with bipolar disorder
Reference 33
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Observation b7123c9e-ae22-4f50-816f-0aa5bd6dd676 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Fast unfold- ing of communities in large networks
Reference 34
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Observation 372bafbd-f33c-453f-83f3-1281c0131479 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Neurogranin enhances synaptic strength through its interaction with calmodulin
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Association between nrgn gene polymorphism and resting-state hippocampal functional connectivity in schizophrenia
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Expression of c1ql3 in discrete neuronal populations controls efferent synapse numbers and diverse behaviors
Reference 37
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Neurod6 expression defines new retinal amacrine cell subtypes and regulates their fate
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Observation 855c492d-a325-4562-84cf-32dbb9e42bb3 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics An rna-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex
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Observation 550e93b0-f2c0-4369-a3f4-762889a3a131 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Purification and characteriza- tion of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse
Reference 40
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Observation f4414ead-07cf-4f14-b280-3803ab30c1dd · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Spatiotemporal transcriptomic atlas of mouse organogenesis using dna nanoball-patterned arrays
Reference 41
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Observation 394918f8-29de-458e-a759-5d04b762ad0e · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Gene expression profiling of atp-binding cassette (abc) transporters as a predictor of the pathologic response to neoadjuvant chemotherapy in breast cancer patients
Reference 42
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Observation 8f32a1c1-d38c-4538-b81d-0c5bfad2f319 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response
Reference 43
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Observation 2afb12bd-fb7a-4562-8ae1-dfb143a67ae5 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics The emerging role of xbp1 in cancer
Reference 44
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Observation 27084cb0-71e2-40fb-9f5b-f3253731f932 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Prognostic impact of agr3 protein expression in breast cancer: A systematic review and meta-analysis
Reference 45
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Observation da1d7ab0-a1ae-4b48-a249-3a248cc0efdd · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics The biomarker he4 (wfdc2) promotes a pro-angiogenic and immunosuppressive tumor microenvironment via regulation of stat3 target genes
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Molecular portraits of human breast tumours
Reference 47
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Tissue-based map of the human proteome
Reference 48
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Observation cfc895ad-88ce-4d11-a732-e75a2b21086b · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Aebp1 con- tributes to breast cancer progression by facilitating cell proliferation, migration, invasion, and blocking apoptosis
Reference 49
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis
Reference 50
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Observation e1b325b2-3c0f-4335-b80e-1793c1bbb9be · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics
Reference 51
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Observation 868ff6dc-28cc-48b8-b0c7-94c58402f7de · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Banksy unifies cell typing and tissue domain segmen- tation for scalable spatial omics data analysis
Reference 52
Source-reported events for the cited work
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Observation 2d4a5d24-6cb0-47ea-a94e-9719d853c336 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Ductal carcinoma in situ: molecular changes accompanying disease progression
Reference 53
Source-reported events for the cited work
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Observation fea1ee16-bfc2-47bf-bb6f-5318e825c317 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Ceacam5 and ceacam6 are major target genes for smad3-mediated tgf-β signaling
Reference 54
Source-reported events for the cited work
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Reference 55
Source-reported events for the cited work
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Observation a2520348-daae-4021-9d22-bf9cc00f9e3e · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Mann-whitney u test
Reference 56
Source-reported events for the cited work
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Foxc2 expres- sion links epithelial–mesenchymal transition and stem cell properties in breast cancer
Reference 57
Source-reported events for the cited work
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Observation 3dced330-b107-47a2-924d-0dcf10fc0134 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Allen brain atlas, 2006
Reference 58
Source-reported events for the cited work
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Observation 7b84fce8-0716-4a08-a5dc-02e4e77258d1 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Defining cell types and states with single-cell genomics
Reference 59
Source-reported events for the cited work
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Observation 55be9aa4-90f7-4239-90d1-c2498a8d4da2 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Cancer statistics, 2024
Reference 60
Source-reported events for the cited work
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Observation 0a534b3c-0b69-446e-949a-648ea395ab76 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Scanpy: large-scale single-cell gene expression data analysis
Reference 61
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Observation 03c7f04a-b648-4d12-9095-a3396811c400 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics GraphMixup: Improving Class-Imbalanced Node Classification on Graphs by Self-supervised Context Prediction
Reference 62
Source-reported events for the cited work
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SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Neural machine translation with gumbel-greedy decoding
Reference 63
Source-reported events for the cited work
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Observation 245c9e3e-c9ca-44f4-9249-0ebf265dd909 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Adam: A method for stochastic optimization
Reference 64
Source-reported events for the cited work
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Observation cdce9191-e01c-4e4f-89f7-fe168c0350b5 · outbound
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Reference 65
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation e6f4e693-eaf7-449e-8e4b-9ec797c39b3e · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Paga: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells
Reference 66
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 1d2a9298-c795-48c0-8a20-6e297809982c · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Alignment and integration of spatial transcriptomics data
Reference 67
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 0cbcc8e8-9c51-4497-a383-296b47610df3 · outbound
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics Inductive representation learning on large graphs
Reference 68
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
No inbound Pith citation observations are available.