ArticleFrontiers in genetics2021
Multi-Omics Data Fusion for Cancer Molecular Subtyping Using Sparse Canonical Correlation Analysis.
Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- OmicsTransformer: self-supervised masked consistency and uncertainty-aware fusion for robust multi-omics prediction.Bioinformatics (Oxford, England) · 2026Article
- Integrating multiomics data using a correlation based graph attention network for subtype classification in lower grade glioma.Discover oncology · 2026Article
- A fusion-based multiomics classification approach for enhanced gene discovery in non-small cell lung cancer.Bioinformatics advances · 2026Article
- A prediction model for platinum-resistant recurrence of ovarian cancer was established using multimodal artificial intelligence machine learning methods.Frontiers in medicine · 2026Article
- Multi-omics research on moyamoya disease: current perspectives and future directions.Nutrition & metabolism · 2025Review
- Bioinformatics Identification and Experimental Validation of a Prognostic Model for the Survival of Lung Squamous Cell Carcinoma Patients.Biochemical genetics · 2025Article
- Powerful significance testing for unbalanced clusters.Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America · 2025Article
- Tumor microenvironment and drug resistance in lung adenocarcinoma: molecular mechanisms, prognostic implications, and therapeutic strategies.Discover oncology · 2025Article
- Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes.Annual review of biomedical data science · 2024Review
- Clustering of HR + /HER2- breast cancer in an Asian cohort is driven by immune phenotypes.Breast cancer research : BCR · 2024Article
- Multi-Omics Integration for Liver Cancer Using Regression Analysis.Current issues in molecular biology · 2024Article
- DMOIT: denoised multi-omics integration approach based on transformer multi-head self-attention mechanism.Frontiers in genetics · 2024Article
- Integration of Multi-Omics Data for the Classification of Glioma Types and Identification of Novel Biomarkers.Bioinformatics and biology insights · 2024Article
- Review
- MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms.Nature communications · 2023Article
- Pancancer survival prediction using a deep learning architecture with multimodal representation and integration.Bioinformatics advances · 2023Article
- Data-driven support to decision-making in molecular tumour boards for lymphoma: A design science approach.Frontiers in oncology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is now clear that major malignancies are heterogeneous diseases associated with diverse molecular properties and clinical outcomes, posing a great challenge for more individualized therapy. In the last decade, cancer molecular subtyping studies were mostly based on transcriptomic profiles, ignoring heterogeneity at other (epi-)genetic levels of gene regulation. Integrating multiple types of (epi)genomic data generates a more comprehensive landscape of biological processes, providing an opportunity to better dissect cancer heterogeneity. Here, we propose sparse canonical correlation analysis for cancer classification (SCCA-CC), which projects each type of single-omics data onto a unified space for data fusion, followed by clustering and classification analysis. Without loss of generality, as case studies, we integrated two types of omics data, mRNA and miRNA profiles, for molecular classification of ovarian cancer (
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