ArticleScientific reports2019
Ontology-based prediction of cancer driver genes.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Establishment of a xenograft model of endometriosis-associated fibrosis using human immortalized endometrial stromal cells overexpressing HOXC8.Scientific reports · 2026Article
- The Potential MicroRNA Diagnostic Biomarkers in Oral Squamous Cell Carcinoma of the Tongue.Current issues in molecular biology · 2024Article
- Identifying new cancer genes based on the integration of annotated gene sets via hypergraph neural networks.Bioinformatics (Oxford, England) · 2024Article
- Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.Journal of molecular evolution · 2023Review
- OncoRTT: Predicting novel oncology-related therapeutic targets using BERT embeddings and omics features.Frontiers in genetics · 2023Article
- RCCC_Pred: A Novel Method for Sequence-Based Identification of Renal Clear Cell Carcinoma Genes through DNA Mutations and a Blend of Features.Diagnostics (Basel, Switzerland) · 2022Article
- EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.Nucleic acids research · 2022Article
- Clinically actionable cancer somatic variants (CACSV): a tumor interpreted dataset for analytical workflows.BMC medical genomics · 2022Article
- Ontologies and Knowledge Graphs in Oncology Research.Cancers · 2022Review
- Improving bioinformatics software quality through incorporation of software engineering practices.PeerJ. Computer science · 2022Article
- Failure to Guard: Mitochondrial Protein Quality Control in Cancer.International journal of molecular sciences · 2021Review
- Prediction of driver variants in the cancer genome via machine learning methodologies.Briefings in bioinformatics · 2021Review
- Semantic similarity and machine learning with ontologies.Briefings in bioinformatics · 2021Review
- A novel computational drug repurposing approach for Systemic Lupus Erythematosus (SLE) treatment using Semantic Web technologies.Saudi journal of biological sciences · 2021Article
- Ontology-based prediction of cancer driver genes.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Identifying and distinguishing cancer driver genes among thousands of candidate mutations remains a major challenge. Accurate identification of driver genes and driver mutations is critical for advancing cancer research and personalizing treatment based on accurate stratification of patients. Due to inter-tumor genetic heterogeneity many driver mutations within a gene occur at low frequencies, which make it challenging to distinguish them from non-driver mutations. We have developed a novel method for identifying cancer driver genes. Our approach utilizes multiple complementary types of information, specifically cellular phenotypes, cellular locations, functions, and whole body physiological phenotypes as features. We demonstrate that our method can accurately identify known cancer driver genes and distinguish between their role in different types of cancer. In addition to confirming known driver genes, we identify several novel candidate driver genes. We demonstrate the utility of our method by validating its predictions in nasopharyngeal cancer and colorectal cancer using whole exome and whole genome sequencing.
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