ArticleDatabase : the journal of biological databases and curation2020
CancerLivER: a database of liver cancer gene expression resources and biomarkers.
Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Comprehensive review of publicly accessible databases for gastrointestinal cancer and future challenges in database construction.Discover oncology · 2026Review
- CPSM: an R package for cancer patient survival risk model using transcriptomics and clinical data.GigaScience · 2026Article
- Unveiling Disparities: Analyzing Hispanic Inclusion in Liver Cancer Research Databases in the United States.Journal of racial and ethnic health disparities · 2025Article
- LiverSCA 2.0: An Enhanced Comprehensive Cell Atlas for Human Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma.Cancers · 2025Article
- Spatial heterogeneity reveals an evolutionary signature predicting therapeutic response and clinical outcomes in hepatocellular carcinoma.Frontiers in bioinformatics · 2025Article
- LiverSCA: A comprehensive and user-friendly cell atlas in human hepatocellular carcinoma.Computational and structural biotechnology journal · 2024Article
- Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration.ACS pharmacology & translational science · 2024Review
- Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach.Bioinformatics and biology insights · 2024Article
- Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.Cancers · 2023Article
- A transcriptomic intratumour heterogeneity-free signature overcomes sampling bias in prognostic risk classification for hepatocellular carcinoma.JHEP reports : innovation in hepatology · 2023Article
- Translational Control of Metabolism and Cell Cycle Progression in Hepatocellular Carcinoma.International journal of molecular sciences · 2023Review
- Targeting Lin28 axis enhances glypican-3-CAR T cell efficacy against hepatic tumor initiating cell population.Molecular therapy : the journal of the American Society of Gene Therapy · 2023Article
- IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma.Computational and structural biotechnology journal · 2023Article
- A critical review of datasets and computational suites for improving cancer theranostics and biomarker discovery.Medical oncology (Northwood, London, England) · 2022Review
- LiqBioer: a manually curated database of cancer biomarkers in body fluid.Database : the journal of biological databases and curation · 2022Article
- GlioMarker: An integrated database for knowledge exploration of diagnostic biomarkers in gliomas.Frontiers in oncology · 2022Article
- Targeting of eIF6-driven translation induces a metabolic rewiring that reduces NAFLD and the consequent evolution to hepatocellular carcinoma.Nature communications · 2021Article
- Non-Coding RNA-Based Biosensors for Early Detection of Liver Cancer.Biomedicines · 2021Review
- Phosphodiesterase 4D Depletion/Inhibition Exerts Anti-Oncogenic Properties in Hepatocellular Carcinoma.Cancers · 2021Article
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4 authors.
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Abstract
Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.
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