ArticleScientific reports2017
A large-scale benchmark of gene prioritization methods.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Survey and improvement strategies for gene prioritization with large language models.Bioinformatics advances · 2025Article
- Random walk with restart on multilayer networks: from node prioritisation to supervised link prediction and beyond.BMC bioinformatics · 2024Article
- A network medicine approach for identifying diagnostic and prognostic biomarkers and exploring drug repurposing in human cancer.Computational and structural biotechnology journal · 2023Article
- Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer.Nature communications · 2022Article
- Construction and contextualization approaches for protein-protein interaction networks.Computational and structural biotechnology journal · 2022Review
- Prioritizing Suggestive Candidate Genes in Migraine: An Opinion.Frontiers in neurology · 2022Article
- WINNER: A network biology tool for biomolecular characterization and prioritization.Frontiers in big data · 2022Article
- Editorial: Towards genome interpretation: Computational methods to model the genotype-phenotype relationship.Frontiers in bioinformatics · 2022Article
- Pharmacogenes that demonstrate high association evidence according to CPIC, DPWG, and PharmGKB.Frontiers in medicine · 2022Article
- Network medicine framework for identifying drug-repurposing opportunities for COVID-19.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Predicting candidate genes from phenotypes, functions and anatomical site of expression.Bioinformatics (Oxford, England) · 2021Article
- The effect of statistical normalization on network propagation scores.Bioinformatics (Oxford, England) · 2021Article
- Network Modeling in Biology: Statistical Methods for Gene and Brain Networks.Statistical science : a review journal of the Institute of Mathematical Statistics · 2021Article
- Network- and systems-based re-engineering of dendritic cells with non-coding RNAs for cancer immunotherapy.Theranostics · 2021Article
- Biological Network Mining.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Network and pathway expansion of genetic disease associations identifies successful drug targets.Scientific reports · 2020Article
- GeneFishing to reconstruct context specific portraits of biological processes.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases.Journal of integrative bioinformatics · 2019Review
- A rectified factor network based biclustering method for detecting cancer-related coding genes and miRNAs, and their interactions.Methods (San Diego, Calif.) · 2019Article
- BEERE: a web server for biomedical entity expansion, ranking and explorations.Nucleic acids research · 2019Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In order to maximize the use of results from high-throughput experimental studies, e.g. GWAS, for identification and diagnostics of new disease-associated genes, it is important to have properly analyzed and benchmarked gene prioritization tools. While prospective benchmarks are underpowered to provide statistically significant results in their attempt to differentiate the performance of gene prioritization tools, a strategy for retrospective benchmarking has been missing, and new tools usually only provide internal validations. The Gene Ontology(GO) contains genes clustered around annotation terms. This intrinsic property of GO can be utilized in construction of robust benchmarks, objective to the problem domain. We demonstrate how this can be achieved for network-based gene prioritization tools, utilizing the FunCoup network. We use cross-validation and a set of appropriate performance measures to compare state-of-the-art gene prioritization algorithms: three based on network diffusion, NetRank and two implementations of Random Walk with Restart, and MaxLink that utilizes network neighborhood. Our benchmark suite provides a systematic and objective way to compare the multitude of available and future gene prioritization tools, enabling researchers to select the best gene prioritization tool for the task at hand, and helping to guide the development of more accurate methods.
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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.