ArticleBMB reports2022
Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen.
Article in BMB reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The trial behind it
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Who cites it
13 citing papers in PubMed, 17 citations in OpenAlex.
- PU-GRAIL: residue-level graph learning for identifying protective bacterial antigens under positive-unlabeled supervision.Bioinformatics (Oxford, England) · 2026Article
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- Identification of severity related mutation hotspots in SARS-CoV-2 using a density-based clustering approach.BioData mining · 2025Article
- In silico screening and experimental validation identify riboflavin as an RNA-targeted antiviral against SARS-CoV-2.Scientific reports · 2025Article
- Severity-specific immune landscape of COVID-19 revealed by single-cell sequencing.Scientific reports · 2025Article
- Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.Scientific reports · 2025Article
- Integrated analysis of COVID-19 multi-omics data for eQTLs reveals genetic mechanisms underlying disease severity.bioRxiv : the preprint server for biology · 2025Article
- EpicPred: predicting phenotypes driven by epitope-binding TCRs using attention-based multiple instance learning.Bioinformatics (Oxford, England) · 2025Article
- Article
- Immunopathological markers and cell types linked to COVID-19 symptom manifestation.BMC infectious diseases · 2024Article
- Denoiseit: denoising gene expression data using rank based isolation trees.BMC bioinformatics · 2024Article
- Subtyping of COVID-19 samples based on cell-cell interaction in single cell transcriptomes.Scientific reports · 2023Article
- COVID-19-Omics Report: From Individual Omics Approaches to Precision Medicine.Reports (MDPI) · 2023Review
Corrections and comments
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Authors and funding
15 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of largescale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment. [BMB Reports 2022; 55(9): 465-471].
Indexed as
Identifiers
35996834PMC9537027W4297459672What 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.