ReviewBiosafety and health2023
Towards precision medicine: Omics approach for COVID-19.
Review in Biosafety and health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Cytokine-Driven Hyperinflammation in Long COVID: Mechanisms, Biomarkers, Complement Dysregulation, and Emerging Immunotherapies-A Narrative Review.Health science reports · 2026Article
- Article
- Precision treatment and frontier advances of glycyrrhizin preparations in drug-induced liver injury (DILI).Frontiers in pharmacology · 2026Review
- Changes in Probiotic Lachnospiraceae Genera Across Different Stages of COVID-19: A Meta-Analysis of 16S rRNA Microbial Data.Microorganisms · 2025Article
- SOCS Proteins: Key Players in Immune Regulation During SARS-CoV-2 Infection.European journal of immunology · 2025Review
- Article
- PathoSeq-QC: a decision support bioinformatics workflow for robust genomic surveillance.Bioinformatics (Oxford, England) · 2025Article
- A theoretical systems chronopharmacology approach for COVID-19: Modeling circadian regulation of lung infection and potential precision therapies.CPT: pharmacometrics & systems pharmacology · 2025Article
- Unlocking the Potential of RNA Sequencing in COVID-19: Toward Accurate Diagnosis and Personalized Medicine.Diagnostics (Basel, Switzerland) · 2025Review
- Rakeiora Genomics Platform: a pathfinder for genomic medicine research in Aotearoa New Zealand.Journal of the Royal Society of New Zealand · 2025Article
- Novel Strategies to Profile SARS-CoV-2 and Human Lung Proteome: Inflammatory Pathways in the Spotlight.BioMed research international · 2025Review
- Serum proteomics and machine learning identify PSMD11 as a prognostic biomarker in severe fever with thrombocytopenia syndrome.Frontiers in immunology · 2025Article
- COVID-19-Omics Report: From Individual Omics Approaches to Precision Medicine.Reports (MDPI) · 2023Review
- Forecast the potential SARS-CoV-2 variants in the future and predict their biological properties and social impacts from bioinformatics and public health perspectives.Biosafety and health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time.
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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.