ReviewMicroorganisms2023
Multiomic Investigations into Lung Health and Disease.
Review in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- Research progress on biomarkers of blast lung injury: Transition from traditional indicators to novel molecular markers.iScience · 2026Review
- The cell with many faces: lung macrophage plasticity and function in response to environmental and pathogenic insults.Physiological reviews · 2026Review
- COPD-Lung Cancer Comorbidity: Mechanistic Insights and Precision Oncology Implications.International journal of chronic obstructive pulmonary disease · 2026Review
- Systems Biology and Multi-Omics in Asthma and COPD: A Systematic Review of Computational Approaches (2010-2024).Journal of asthma and allergy · 2026Review
- Review
- The key players of inflammasomes and pyroptosis in sepsis-induced pathogenesis and organ dysfunction.Frontiers in pharmacology · 2025Review
- Statistical and machine learning approaches for identifying biomarker associations in respiratory diseases in a population-specific region.Frontiers in artificial intelligence · 2025Article
- Cell death in acute lung injury: caspase-regulated apoptosis, pyroptosis, necroptosis, and PANoptosis.Frontiers in pharmacology · 2025Review
- Exploring Molecular Mechanisms and Biomarkers in COPD: An Overview of Current Advancements and Perspectives.International journal of molecular sciences · 2024Review
- Macrophage biomimetic nanoparticle-targeted functional extracellular vesicle micro-RNAs revealed via multiomics analysis alleviate sepsis-induced acute lung injury.Journal of nanobiotechnology · 2024Article
- Mitochondrial Dysfunction in Chronic Obstructive Pulmonary Disease: Unraveling the Molecular Nexus.Biomedicines · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.
Indexed as
Identifiers
What OpenQuestion holds
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.