ArticleNucleic acids research2018
TissGDB: tissue-specific gene database in cancer.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- TBCancer: A database for exploring characteristics and functions of tissue-biased genes in cancer.iMetaOmics · 2025Article
- MIPD: Molecules, Imagings, and Clinical Phenotype Integrated Database.Database : the journal of biological databases and curation · 2025Article
- Multi-omics analysis reveals criticaliScience · 2025Article
- Microglial Lyzl4 Facilitates β-Amyloid Clearance in Alzheimer's Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- The human retroviral-like aspartic protease 1 (ASPRV1): From in vitro studies to clinical correlations.The Journal of biological chemistry · 2024Review
- Single-Cell Transcriptomics Reveals Pre-existing COVID-19 Vulnerability Factors in Lung Cancer Patients.Molecular cancer research : MCR · 2024Article
- A transcriptome based molecular classification scheme for cholangiocarcinoma and subtype-derived prognostic biomarker.Nature communications · 2024Article
- Omada: robust clustering of transcriptomes through multiple testing.GigaScience · 2024Article
- Artificial intelligence and neoantigens: paving the path for precision cancer immunotherapy.Frontiers in immunology · 2024Review
- Gene regulatory network inference based on causal discovery integrating with graph neural network.Quantitative biology (Beijing, China) · 2023Article
- Comparative RNA-Seq Analysis Revealed Tissue-Specific Splicing Variations during the Generation of the PDX Model.International journal of molecular sciences · 2023Article
- Transcriptomic analysis reveals a tissue-specific loss of identity during ageing and cancer.BMC genomics · 2023Article
- ProInfer: An interpretable protein inference tool leveraging on biological networks.PLoS computational biology · 2023Article
- HetIG-PreDiG: A Heterogeneous Integrated Graph Model for Predicting Human Disease Genes based on gene expression.PloS one · 2023Article
- COVIDanno, COVID-19 annotation in human.Frontiers in microbiology · 2023Article
- Robust and rigorous identification of tissue-specific genes by statistically extending tau score.BioData mining · 2022Article
- WebCSEA: web-based cell-type-specific enrichment analysis of genes.Nucleic acids research · 2022Article
- Pan-cancer analyses reveal the genetic and pharmacogenomic landscape of transient receptor potential channels.NPJ genomic medicine · 2022Article
- SRTdb: an omnibus for human tissue and cancer-specific RNA transcripts.Biomarker research · 2022Article
- Article
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Authors and funding
6 authors.
Funding
Abstract
Tissue-specific gene expression is critical in understanding biological processes, physiological conditions, and disease. The identification and appropriate use of tissue-specific genes (TissGenes) will provide important insights into disease mechanisms and organ-specific therapeutic targets. To better understand the tissue-specific features for each cancer type and to advance the discovery of clinically relevant genes or mutations, we built TissGDB (Tissue specific Gene DataBase in cancer) available at http://zhaobioinfo.org/TissGDB. We collected and curated 2461 tissue specific genes (TissGenes) across 22 tissue types that matched the 28 cancer types of The Cancer Genome Atlas (TCGA) from three representative tissue-specific gene expression resources: The Human Protein Atlas (HPA), Tissue-specific Gene Expression and Regulation (TiGER), and Genotype-Tissue Expression (GTEx). For these 2461 TissGenes, we performed gene expression, somatic mutation, and prognostic marker-based analyses across 28 cancer types using TCGA data. Our analyses identified hundreds of TissGenes, including genes that universally kept or lost tissue-specific gene expression, with other features: cancer type-specific isoform expression, fusion with oncogenes or tumor suppressor genes, and markers for protective or risk prognosis. TissGDB provides seven categories of annotations: TissGeneSummary, TissGeneExp, TissGene-miRNA, TissGeneMut, TissGeneNet, TissGeneProg, TissGeneClin.
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Registered trials
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.