Evidence map›Paper›PMID 35801633›Full record

ReviewVirulence2022

The role of multi-omics in the diagnosis of COVID-19 and the prediction of new therapeutic targets.

Jianli Ma, Yuwei Deng, Minghui Zhang, Jinming Yu

Open access · goldAbstract readReview
In one paragraph

Review in Virulence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.8field-weighted citation impact, top 13% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 18 citations in OpenAlex.

  1. Multi-omics to study chronic respiratory diseases and viral infections.European respiratory review : an official journal of the European Respiratory Society · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Jianli MaDepartment of Radiation Oncology, Shandong University Cancer Center, Jinan, Shandong Province, People's Republic of China.
Yuwei DengDepartment of Breast Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, People's Republic of China.
Minghui ZhangDepartment of Respiratory Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang Province, People's Republic of China.
Jinming YuDepartment of Radiation Oncology, Shandong University Cancer Center, Jinan, Shandong Province, People's Republic of China.
Shandong University · CNThird Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing COVID-19, has led to more than 170 million confirmed cases in 223 countries and regions, claiming 3,872,457 lives. Some patients with COVID-19 have mild clinical symptoms despite severe respiratory failure, which greatly increases the difficulty of diagnosis and treatment. It is therefore necessary to identify biological characteristics of SARS-CoV-2, screen novel diagnostic and prognostic biomarkers, as well as to explore potential therapeutic targets for COVID-19. In this comprehensive review, we discuss the current published literature on COVID-19. We find that the comprehensive application of genomics, transcriptomics, proteomics and metabolomics is becoming increasingly important in the treatment of COVID-19. Multi-omics analysis platforms are expected to revolutionize the diagnosis and classification of COVID-19. This review aims to provide a reference for diagnosis, surveillance and clinical decision making related to COVID-19.

Indexed as

COVID-19HumansPandemicsSARS-CoV-2COVID-19genomicsmetabolomicsmulti-omicsproteomicstranscriptomic

Identifiers

PMID35801633
PMCPMC9272836
OpenAlexW4284890271

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.