ReviewAnimal cells and systems2020
How to interpret and integrate multi-omics data at systems level.
Review in Animal cells and systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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.
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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
22 citing papers in PubMed.
- Review
- Allergic Respiratory Diseases in the Climate Change Context: Aerobiological Tools and Projections as Preventive Actions for Pollen-Induced Allergies.Medical sciences (Basel, Switzerland) · 2026Review
- Exercise-specific post-translational modification signatures: unveiling precise regulatory mechanisms of molecular exercise language and cellular adaptation.Frontiers in sports and active living · 2026Review
- Multi-omics integration in allergy, viral infections and asthma: a comprehensive analysis of bioinformatics tools.Frontiers in bioinformatics · 2026Article
- Decoding Multi-Omics Signatures in Lower-Grade Glioma Using Protein-Protein Interaction-Informed Graph Attention Networks and Ensemble Learning.Diagnostics (Basel, Switzerland) · 2025Article
- Systematic data analysis pipeline for quantitative morphological cell phenotyping.Computational and structural biotechnology journal · 2024Review
- Redefining Roles: A Paradigm Shift in Tryptophan-Kynurenine Metabolism for Innovative Clinical Applications.International journal of molecular sciences · 2024Review
- Revealing the dynamic changes of metabolites and molecular mechanisms of chlorogenic acid accumulation during the leaf development ofFrontiers in plant science · 2024Article
- Beethoven, Infected with Hepatitis B, Inspired the "Beethoven Virus."Molecules and cells · 2023Article
- A Role of Multi-Omics Technologies in Sheep and Goat Meats: Progress and Way Ahead.Foods (Basel, Switzerland) · 2023Review
- Multi-Omics Approaches to Improve Meat Quality and Taste Characteristics.Food science of animal resources · 2023Review
- Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer.Frontiers in genetics · 2023Article
- Human Endogenous Retroviruses: Friends and Foes in Urology Clinics.International neurourology journal · 2022Article
- Omics Data and Data Representations for Deep Learning-Based Predictive Modeling.International journal of molecular sciences · 2022Review
- Computational approaches for network-based integrative multi-omics analysis.Frontiers in molecular biosciences · 2022Review
- Characterization of differential gene expression of broiler chicken to thermal stress in discrete developmental stages.Animal cells and systems · 2022Article
- Human Endogenous Retroviruses as Gene Expression Regulators: Insights from Animal Models into Human Diseases.Molecules and cells · 2021Review
- Let Them Flourish for the First Weeks and Suffer LessMolecules and cells · 2021Article
- Sure, Fathers Give Birth, Too! Postnatal paternal folate deficiency increases congenital disabilities through H3K4me3 histone methylation changes in sperm and embryos.Molecules and cells · 2021Article
- Multi-omic signatures of atherogenic dyslipidaemia: pre-clinical target identification and validation in humans.Journal of translational medicine · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current parallel sequencing technologies generate biological sequence data explosively and enable omics studies that analyze collective biological features. The more omics data that is accumulated, the more they show the regulatory complexity of biological phenotypes. This high order regulatory complexity needs systems-level approaches, including network analysis, to understand it. There are a series of layers in the omics field that are closely connected to each other as described in 'central dogma.' We, therefore, have to not only interpret each single omics layer but also to integrate multi-omics layers systematically to get a full picture of the regulatory landscape of the biological phenotype. Especially, individual omics data has their own adequate biological network to apply systematic analysis appropriately. A full regulatory landscape can only be obtained when multi-omics data are incorporated within adequate networks. In this review, we discuss how to interpret and integrate multi-omics data systematically using recent studies. We also propose an analysis framework for systematic multi-omics interpretation by centering on the transcriptional core regulator, which can be incorporated in all omics networks.
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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.