ArticleNucleic acids research2024
DriverDBv4: a multi-omics integration database for cancer driver gene research.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
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- Comprehensive review of publicly accessible databases for gastrointestinal cancer and future challenges in database construction.Discover oncology · 2026Review
- Epigenomics-Guided Multi-Omics Integration Uncovers a Lipid-Metabolic Signature with Translational Utility in Bladder Cancer.Computational and structural biotechnology journal · 2026Article
- Multi-omics strategies for biomarker discovery and application in personalized oncology.Molecular biomedicine · 2025Review
- Integrative multi-omics and preclinical analyses identify miR-4776-5p as a prognostic radiosensitizer for patients undergoing radiotherapy for head-and-neck cancer.Discover oncology · 2025Article
- Ether-lipids accumulation promotes hepatocellular carcinoma progression linked to PPARα deficiency.Journal of biomedical science · 2025Article
- Complete reference genome and pangenome improve genome-wide detection and interpretation of DNA methylation using sequencing and array data.Cell reports · 2025Article
- Exploring potential biomarkers and lead molecules in gastric cancer by network biology, drug repurposing and virtual screening strategies.Molecular diversity · 2025Article
- Explainable AI Model Reveals Informative Mutational Signatures for Cancer-Type Classification.Cancers · 2025Article
- Memory-promoting function of miR-379-5p attenuates CD8Journal for immunotherapy of cancer · 2025Article
- MRPL24 drives breast cancer metastasis and stemness by targeting c-MYC, BRD4, and STAT3.3 Biotech · 2025Article
- TMPO-AS1-hsa-let-7b-5p-EZH2-RNA network predicts poor survival in basal-like breast cancer patients.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2025Article
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- Enhancing Molecular Network-Based Cancer Driver Gene Prediction Using Machine Learning Approaches: Current Challenges and Opportunities.Journal of cellular and molecular medicine · 2025Review
- Bioinformatics insights intoFrontiers in cell and developmental biology · 2025Article
- Exploring the function and prognostic value of RPLP0, RPLP1 and RPLP2 expression in lung adenocarcinoma.Journal of molecular histology · 2024Article
- Whole-exome sequencing reveals novel genomic signatures and potential therapeutic targets during the progression of rectal neuroendocrine neoplasm.Cell death & disease · 2024Article
- Precision oncology platforms: practical strategies for genomic database utilization in cancer treatment.Molecular cytogenetics · 2024Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.bioinfomics.org/). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.
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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.