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975
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ShareScore release 0.9.0
Dataset results
975 results for “Spatial transcriptomics”
Mapping the spatial transcriptomic signature of the hippocampus during memory consolidation
GEO Series GSE223066. Mus musculus. 34 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Spatial Transcriptomics Uncovers Brain Region-Specific Transcriptional Changes Associated with Development and Aging
GEO Series GSE287202. Mus musculus. 6 samples. Type: Other.
Single-cell and spatial transcriptomics characterisation of the immunological landscape in the healthy and PSC human liver
GEO Series GSE243977. Homo sapiens. 26 samples. Type: Expression profiling by high throughput sequencing.
Spatial Transcriptomics of Human Fetal Lungs
GEO Series GSE310610. Homo sapiens. 12 samples. Type: Other.
A Lactate-induced SREBF2-dependent genetic program drives an immunotolerant dendritic cell population during cancer progression [Spatial transcriptomics]
GEO Series GSE253588. Homo sapiens. 3 samples. Type: Other.
Injury-Induced CLU-Positive Cardiomyocytes Drive Metabolic Reprogramming of Macrophage Function in Heart Regeneration [Spatial Transcriptomics]
GEO Series GSE254055. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Spatial transcriptomics for high-grade serous ovarian carcinoma who were treated with Olaparib maintenance therapy
GEO Series GSE288483. Homo sapiens. 8 samples. Type: Other.
Integrative analysis of spatial and single-cell transcriptome data from human pancreatic cancer reveals an intermediate cancer cell population associated with poor prognosis_Spatial H&E images
<p>High-resolution H&E images of spatial transcriptome data</p>
Output files for 'Multiscale topology classifies cells in subcellular spatial transcriptomics'
<p>This data set contains output files for the paper 'Multiscale topology classifies cells in subcellular spatial transcriptomics'. See the READMEs included for each experiment subdirectory.</p>
SpaMask: Dual Masking Graph Autoencoder with Contrastive Learning for Spatial Transcriptomics
<p>Understanding the spatial locations of cell within tissues is crucial for unraveling the organization of cellular diversity. Recent advancements in spatial resolved transcriptomics (SRT) have enabled the analysis of gene expression while preserving the spatial context within tissues. Spatial domain characterization is a critical first step in SRT data analysis, providing the foundation for subsequent analyses and insights into biological implications. Graph neural networks (GNNs) have emerged as a common tool for addressing this challenge due to the structural nature of SRT data. However, current graph-based deep learning approaches often overlook the instability caused by the high sparsity of SRT data. <strong>Masking mechanisms</strong>, as an effective self-supervised learning strategy, can enhance the robustness of these models. To this end, we propose <strong>SpaMask, dual masking graph autoencoder with contrastive learning for SRT analysis</strong>. Unlike previous GNNs, SpaMask masks a portion of spot nodes and spot-to-spot edges to enhance its performance and robustness. SpaMask combines <strong>Masked Graph Autoencoders (MGAE) and Masked Graph Contrastive Learning (MGCL)</strong> modules, with MGAE using node masking to leverage spatial neighbors for improved clustering accuracy, while MGCL applies edge masking to create a contrastive loss framework that tightens embeddings of adjacent nodes based on spatial proximity and feature similarity. We conducted a comprehensive evaluation of SpaMask on <strong>eight datasets from five different platforms</strong>. Compared to existing methods, SpaMask achieves superior clustering accuracy and effective batch correction.</p>
Dataset of spatial transcriptomics of lung adenocarcinoma for analyzing the tumor microenvironment using topological analysis
<p>The human lung adenocarcinoma dataset for 'STopover captures spatial colocalization and interaction in the tumor microenvironment using topological analysis in spatial transcriptomics data'. </p>
Spatially Resolved IBD: Spatial Transcriptomics of Inflammatory Bowel Disease (IBD)
ClinicalTrials.gov study NCT06484738. IPD Sharing: NO. Countries: 1. Publications: 0.
Mechanistic Studies of Chronic COPD Using Single-Cell Sequencing and Single-Cell Spatial Transcriptomics
ClinicalTrials.gov study NCT07208123. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Prediction of Therapeutic Response to Neoadjuvant Chemotherapy in Muscle Invasive Bladder Cancer Patients Using Spatial Transcriptomics
ClinicalTrials.gov study NCT06373055. IPD Sharing: NO. Countries: 1. Publications: 0.
Prospective Study for Molecular Biomarkers and Spatial Transcriptomics of Nasopharyngeal Carcinoma
ClinicalTrials.gov study NCT05912582. IPD Sharing: YES. Countries: 1. Publications: 0.
Spatial Transcriptomics in Kidney Transplantation
ClinicalTrials.gov study NCT06288425. IPD Sharing: NO. Countries: 1. Publications: 0.
Spatial RadiomIcs and TRanscriptomics to the DIscovery of the Cross-link Between Colon Cancer and ChrOnic Kidney Disease
ClinicalTrials.gov study NCT06886282. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Seattle Spatial Transcriptomic Research in Inflammatory Bowel Disease Evaluation (STRIDE)
ClinicalTrials.gov study NCT06315179. IPD Sharing: NO. Countries: 1. Publications: 0.
IDH-mutant gliomas arise from glial progenitor cells harboring the initial driver mutation (Related accession no. GSE275791) - Spatial transcriptomics dataset
GEO Series GSE302642. Homo sapiens. 6 samples. Type: Other.
Spatial transcriptomics revealed that S1pr2 deletion in keratinocytes increases the MyD88/NF-kB pathway and psoriasis-related cytokine expression in the epidermis
GEO Series GSE277246. Mus musculus. 2 samples. Type: Other.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.