ArticleJournal of translational medicine2024
Multi-omics integration with weighted affinity and self-diffusion applied for cancer subtypes identification.
Article in Journal of translational medicine, 2024. 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.
- Article
- CEDR: robust consensus cancer subtyping with multi-omics data via ensemble dimensionality reduction.Briefings in bioinformatics · 2026Article
- A unified framework for correcting batch effects and integrating multi-omics data.Scientific reports · 2026Article
- SeOMLR: one-step multi-view latent representation with self-weighted ensemble learning for multi-omics cancer subtyping.Bioinformatics (Oxford, England) · 2026Article
- CancerSubtypeXplore: A Modular Platform for Multiomics Cancer Subtype Prediction and Biomarker Consensus Discovery.Computational and structural biotechnology journal · 2026Article
- ULSL: Unified Latent and Similarity Learning for robust multi-omics cancer subtype identification.Bioinformatics advances · 2026Article
- The role of MiRNA-mediated tumor microenvironment in bone metastasis from a multi-omics perspective: cross-cancer mechanisms and clinical translation.Frontiers in oncology · 2026Review
- MOTLAB: A Weighted Multi-Omics Transfer Learning Approach to Mitigate Breast Cancer Racial Disparities.bioRxiv : the preprint server for biology · 2025Article
- Confounder-Adjusted Differentiation of Colorectal Cancer via Dynamic Propagation of Pathway Influence.International journal of molecular sciences · 2025Article
- Uncovering the Understanding of the Concept of Patient Similarity in Cancer Research and Treatment: Scoping Review.Journal of medical Internet research · 2025Article
- Comprehensive Evaluation of Multi-Omics Clustering Algorithms for Cancer Molecular Subtyping.International journal of molecular sciences · 2025Article
- Article
- Applications and advances of multi-omics technologies in gastrointestinal tumors.Frontiers in medicine · 2025Review
- PartIES: a disease subtyping framework with Partition-level Integration using diffusion-Enhanced Similarities from multi-omics Data.Briefings in bioinformatics · 2024Article
- Mechanisms and technologies in cancer epigenetics.Frontiers in oncology · 2024Review
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Authors and funding
3 authors.
Funding
Abstract
backgroundCharacterizing cancer molecular subtypes is crucial for improving prognosis and individualized treatment. Integrative analysis of multi-omics data has become an important approach for disease subtyping, yielding better understanding of the complex biology. Current multi-omics integration tools and methods for cancer subtyping often suffer challenges of high computational efficiency as well as the problem of weight assignment on data types.
resultsHere, we present an efficient multi-omics integration via weighted affinity and self-diffusion (MOSD) to dissect cancer heterogeneity. MOSD first construct local scaling affinity on each data type and then integrate all affinities by weighted linear combination, followed by the self-diffusion to further improve the patients' similarities for the downstream clustering analysis. To demonstrate the effectiveness and usefulness for cancer subtyping, we apply MOSD across ten cancer types with three measurements (Gene expression, DNA methylation, miRNA).
conclusionsOur approach exhibits more significant differences in patient survival and computationally efficient benchmarking against several state-of-art integration methods and the identified molecular subtypes reveal strongly biological interpretability. The code as well as its implementation are available in GitHub: https://github.com/DXCODEE/MOSD .
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