ArticleGenome biology2018
Tensorial blind source separation for improved analysis of multi-omic data.
Article in Genome biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Deep learning facilitated discovery of prognosis biomarkers and their ligands to improve liver cancer treatment.International journal of surgery (London, England) · 2026Article
- Augmented kurtosis-based projection pursuit: a novel, advanced machine learning approach for multi-omics data analysis and integration.Nucleic acids research · 2025Article
- stImage: a versatile framework for optimizing spatial transcriptomic analysis through customizable deep histology and location informed integration.Briefings in bioinformatics · 2025Article
- Cell-type-specific subtyping of epigenomes improves prognostic stratification of cancer.Genome medicine · 2025Article
- Interpretable deep learning of single-cell and epigenetic data reveals novel molecular insights in aging.Scientific reports · 2025Article
- SiRCle (Signature Regulatory Clustering) model integration reveals mechanisms of phenotype regulation in renal cancer.Genome medicine · 2024Article
- Integrative analysis of multi-omics data reveals importance of collagen and the PI3K AKT signalling pathway in CAKUT.Scientific reports · 2024Article
- An improved epigenetic counter to track mitotic age in normal and precancerous tissues.Nature communications · 2024Article
- Joint multi-omics discriminant analysis with consistent representation learning using PANDA.Research square · 2024Article
- Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.Nature genetics · 2024Article
- LIBRA: an adaptative integrative tool for paired single-cell multi-omics data.Quantitative biology (Beijing, China) · 2023Article
- Phenomics and Robust Multiomics Data for Cardiovascular Disease Subtyping.Arteriosclerosis, thrombosis, and vascular biology · 2023Review
- Network-based integration of multi-omics data for clinical outcome prediction in neuroblastoma.Scientific reports · 2022Article
- Multi-dimensional data integration algorithm based on random walk with restart.BMC bioinformatics · 2021Article
- Benchmarking joint multi-omics dimensionality reduction approaches for the study of cancer.Nature communications · 2021Article
- Integrative approaches for analysis of mRNA and microRNA high-throughput data.Computational and structural biotechnology journal · 2021Review
- Independent Component Analysis for Unraveling the Complexity of Cancer Omics Datasets.International journal of molecular sciences · 2019Review
- Molecular Inverse Comorbidity between Alzheimer's Disease and Lung Cancer: New Insights from Matrix Factorization.International journal of molecular sciences · 2019Article
- Cell lineage and communication network inference via optimization for single-cell transcriptomics.Nucleic acids research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
There is an increased need for integrative analyses of multi-omic data. We present and benchmark a novel tensorial independent component analysis (tICA) algorithm against current state-of-the-art methods. We find that tICA outperforms competing methods in identifying biological sources of data variation at a reduced computational cost. On epigenetic data, tICA can identify methylation quantitative trait loci at high sensitivity. In the cancer context, tICA identifies gene modules whose expression variation across tumours is driven by copy-number or DNA methylation changes, but whose deregulation relative to normal tissue is independent of such alterations, a result we validate by direct analysis of individual data types.
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Registered trials
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.