ArticleBioData mining2017
Meta-analytic support vector machine for integrating multiple omics data.
Article in BioData mining, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 108 papers, 3 of them syntheses that pooled it.
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Who cites it
108 citing papers in PubMed, 3 syntheses or guidelines pooled it.
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- SUCLG1 mutations and mitochondrial encephalomyopathy: a case study and review of the literature.Molecular biology reports · 2020Pooled it
- Meta-Analysis Based on Nonconvex Regularization.Scientific reports · 2020Pooled it
- Germline Variation and Somatic Alterations in Ewing Sarcoma.Methods in molecular biology (Clifton, N.J.) · 2027Article
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- Delineating the Genetic Basis of RNF213-related vasculopathies: The association of PKHD1 variants with bilateral cerebral vasculopathy.European journal of human genetics : EJHG · 2026Article
- ACVI-Med, an open source variant interpretation tool for medical genomics.BMC bioinformatics · 2026Article
- MissenseHMM: state-based annotations for missense variants through joint modeling of pathogenicity scores.bioRxiv : the preprint server for biology · 2026Article
- De novo variants in the splicing factor gene SF3B1 are associated with neurodevelopmental disorders.Nature communications · 2026Article
- DBP-CanPred: a machine learning model for predicting cancer-causing mutations in DNA-binding proteins.Frontiers in bioinformatics · 2026Article
- MutAnt: mutation annotation tool predicts deleteriousness of missense mutations and improves mutation calling from transcriptomics.Human genetics · 2025Article
- Plant-pathogen interactions: making the case for multi-omics analysis of complex pathosystems.Stress biology · 2025Review
- Mosaic variants of neurodevelopmental and mitochondrial genes in postmortem paraventricular thalamus in bipolar disorder detected by deep exome sequencing.Psychiatry and clinical neurosciences · 2025Article
- Data Interoperability and Harmonization in Cardiovascular Genomic and Precision Medicine.Circulation. Genomic and precision medicine · 2025Review
- Germline PARN Variants in Telomere Biology Disorders and Challenges in Variant Curation.Molecular genetics & genomic medicine · 2025Article
- Low T cell diversity associates with poor outcome in bladder cancer: A comprehensive longitudinal analysis of the T cell receptor repertoire.Cell reports. Medicine · 2025Article
- Dynamic clustering of genomics cohorts beyond race, ethnicity-and ancestry.BMC medical genomics · 2025Article
- Missense variants pathogenicity annotation from homologous proteins.Bioinformatics (Oxford, England) · 2025Article
- CommonGenome research · 2025Article
48 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOf late, high-throughput microarray and sequencing data have been extensively used to monitor biomarkers and biological processes related to many diseases. Under this circumstance, the support vector machine (SVM) has been popularly used and been successful for gene selection in many applications. Despite surpassing benefits of the SVMs, single data analysis using small- and mid-size of data inevitably runs into the problem of low reproducibility and statistical power. To address this problem, we propose a meta-analytic support vector machine (Meta-SVM) that can accommodate multiple omics data, making it possible to detect consensus genes associated with diseases across studies.
resultsExperimental studies show that the Meta-SVM is superior to the existing meta-analysis method in detecting true signal genes. In real data applications, diverse omics data of breast cancer (TCGA) and mRNA expression data of lung disease (idiopathic pulmonary fibrosis; IPF) were applied. As a result, we identified gene sets consistently associated with the diseases across studies. In particular, the ascertained gene set of TCGA omics data was found to be significantly enriched in the ABC transporters pathways well known as critical for the breast cancer mechanism.
conclusionThe Meta-SVM effectively achieves the purpose of meta-analysis as jointly leveraging multiple omics data, and facilitates identifying potential biomarkers and elucidating the disease process.
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