ReviewComputational and structural biotechnology journal2020
On fusion methods for knowledge discovery from multi-omics datasets.
Review in Computational and structural biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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
13 citing papers in PubMed.
- Machine Learning and Multi-Omics Integration to Reveal Biomarkers and Microbial Community Assembly Differences in Abnormal Stacking Fermentation of Sauce-FlavorFoods (Basel, Switzerland) · 2025Article
- Digital psychiatry: concepts, framework, and implications.Frontiers in psychiatry · 2025Review
- Ten quick tips for avoiding pitfalls in multi-omics data integration analyses.PLoS computational biology · 2023Article
- Towards Decoding Hepatotoxicity of Approved Drugs through Navigation of Multiverse and Consensus Chemical Spaces.Biomolecules · 2023Article
- High-dimensional gene expression and morphology profiles of cells across 28,000 genetic and chemical perturbations.Nature methods · 2022Article
- Article
- Challenges in translational machine learning.Human genetics · 2022Review
- Transcriptional Biomarkers and Immunohistochemistry for Detection of Illicit Dexamethasone Administration in Veal Calves.Foods (Basel, Switzerland) · 2022Article
- NHLBI-CMREF Workshop Report on Pulmonary Vascular Disease Classification: JACC State-of-the-Art Review.Journal of the American College of Cardiology · 2021Review
- A Detailed Catalogue of Multi-Omics Methodologies for Identification of Putative Biomarkers and Causal Molecular Networks in Translational Cancer Research.International journal of molecular sciences · 2021Review
- Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis.Computational and structural biotechnology journal · 2021Review
- Tensor-Decomposition-Based Unsupervised Feature Extraction Applied to Prostate Cancer Multiomics Data.Genes · 2020Article
- State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing.Frontiers in genetics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Recent years have witnessed the tendency of measuring a biological sample on multiple omics scales for a comprehensive understanding of how biological activities on varying levels are perturbed by genetic variants, environments, and their interactions. This new trend raises substantial challenges to data integration and fusion, of which the latter is a specific type of integration that applies a uniform method in a scalable manner, to solve biological problems which the multi-omics measurements target. Fusion-based analysis has advanced rapidly in the past decade, thanks to application drivers and theoretical breakthroughs in mathematics, statistics, and computer science. We will briefly address these methods from methodological and mathematical perspectives and categorize them into three types of approaches: data fusion (a narrowed definition as compared to the general data fusion concept), model fusion, and mixed fusion. We will demonstrate at least one typical example in each specific category to exemplify the characteristics, principles, and applications of the methods in general, as well as discuss the gaps and potential issues for future studies.
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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.