ArticleNucleic acids research2022
CancerSCEM: a database of single-cell expression map across various human cancers.
Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers, 2 of them syntheses that pooled it.
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Who cites it
71 citing papers in PubMed, 2 syntheses or guidelines pooled it, 135 citations in OpenAlex.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Synthetic lethal gene pairs: Experimental approaches and predictive models.Frontiers in genetics · 2022Pooled it
- Loss of NCCRP1 overcomes immune evasion in lung adenocarcinoma.Journal for immunotherapy of cancer · 2026Article
- Article
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- A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping.bioRxiv : the preprint server for biology · 2026Article
- Mitochondrial autophagy mechanism and berberine therapeutic target discovery in hepatocellular carcinoma based on single-cell and transcriptome analysis.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- huSA: a comprehensive database for multi-dimensional resolution of bulk, single cell and spatial transcription profiles in skin diseases.Database : the journal of biological databases and curation · 2026Article
- TE-SCALE: a comprehensive database for exploring transposable element expression across human cancers at single-cell resolution.Nucleic acids research · 2026Article
- RNAPaceDB: a dedicated database to dissect RNA velocity across diverse cell types.Nucleic acids research · 2026Article
- An integrative omics-guided druggability analysis of VCX2 in hepatocellular carcinoma using Peruvian natural products.Frontiers in bioinformatics · 2026Article
- Integrating single-cell transcriptomics with deep learning for glioblastoma treatment.Frontiers in genetics · 2026Review
- Interpretable phenotype decoding from multicondition sequencing data with ALPINE.Genome research · 2025Article
- Adaptive resampling for improved machine learning in imbalanced single-cell datasets.bioRxiv : the preprint server for biology · 2025Article
- Panmim: a resource of pan-cancer metastasis immune microenvironment.Journal of translational medicine · 2025Article
- ARHGAP11A, a member of Rho GTPase activating protein family, as a prognostic biomarker linked to DNA damage response across pan-cancer.BMC cancer · 2025Article
- Large Language Models for Translational Cancer Informatics.JCO clinical cancer informatics · 2025Review
- Mesenchymal stroma drives axonogenesis and nerve-induced aggressiveness in osteosarcoma.Journal of experimental & clinical cancer research : CR · 2025Article
- Tumour Single-Cell Bioinformatics: From Immune Profiling to Molecular Dynamics.Journal of cellular and molecular medicine · 2025Review
- A pan-cancer atlas of therapeutic T cell targets.bioRxiv : the preprint server for biology · 2025Article
11 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the proliferating studies of human cancers by single-cell RNA sequencing technique (scRNA-seq), cellular heterogeneity, immune landscape and pathogenesis within diverse cancers have been uncovered successively. The exponential explosion of massive cancer scRNA-seq datasets in the past decade are calling for a burning demand to be integrated and processed for essential investigations in tumor microenvironment of various cancer types. To fill this gap, we developed a database of Cancer Single-cell Expression Map (CancerSCEM, https://ngdc.cncb.ac.cn/cancerscem), particularly focusing on a variety of human cancers. To date, CancerSCE version 1.0 consists of 208 cancer samples across 28 studies and 20 human cancer types. A series of uniformly and multiscale analyses for each sample were performed, including accurate cell type annotation, functional gene expressions, cell interaction network, survival analysis and etc. Plus, we visualized CancerSCEM as a user-friendly web interface for users to browse, search, online analyze and download all the metadata as well as analytical results. More importantly and unprecedentedly, the newly-constructed comprehensive online analyzing platform in CancerSCEM integrates seven analyze functions, where investigators can interactively perform cancer scRNA-seq analyses. In all, CancerSCEM paves an informative and practical way to facilitate human cancer studies, and also provides insights into clinical therapy assessments.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.