Evidence map›Paper›PMID 33198594›Full record

ArticlePathogens and global health2020

Immunodominant regions prediction of nucleocapsid protein for SARS-CoV-2 early diagnosis: a bioinformatics and immunoinformatics study.

Yufeng Dai, Hongzhi Chen, Siqi Zhuang, Xiaojing Feng, Yiyuan Fang, Haoneng Tang, Ruchun Dai, Lingli Tang, Jun Liu, Tianmin Ma and 1 more

Open access · greenAbstract read
In one paragraph

Article in Pathogens and global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

15 citing papers in PubMed, 25 citations in OpenAlex.

  1. Frontiers in microbiology · 2026
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  5. Hybridization-driven fluorometric platform based on metal-organic frameworks for the identification of the highly homologous viruses.Microchemical journal : devoted to the application of microtechniques in all branches of science · 2023
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  6. Review
  7. Article
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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

11 authors at 4 institutions in 3 countries.

Yufeng DaiDepartment of Laboratory Medicine, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Hongzhi ChenNational Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, Metabolic Syndrome Research Center, and Department of Metabolism and Endocrinology, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Siqi ZhuangDepartment of Laboratory Medicine, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Xiaojing FengDepartment of Laboratory Medicine, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Yiyuan FangDepartment of Laboratory Medicine, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Haoneng TangDepartment of Laboratory Medicine, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Ruchun DaiNational Clinical Research Center for Metabolic Diseases, Hunan Provincial Key Laboratory for Metabolic Bone Diseases, Department of Metabolism and Endocrinology, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Lingli TangDepartment of Laboratory Medicine, the Second Xiangya Hospital, Central South University , Changsha, Hunan, China.
Jun LiuDepartment of Radiology, The Second Xiangya Hospital, Central South University , Changsha, Hunan, 410011, China.
Tianmin MaAsian International Collaboration, Waitemata District Health Board, New Zealand, Level 1 , Auckland, 15 Shea Terrace, 0622, New Zealand.
Guangming ZhongDepartment of Microbiology and Immunology, University of Texas Health Science Center at San Antonio , San Antonio,TX, 7703 Floyd Curl Drive, 78229, USA.
Central South University · CNSecond Xiangya Hospital of Central South University · CNThe University of Texas Health Science Center at San Antonio · USWaitemata District Health Board · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 caused by SARS-CoV-2 is sweeping the world and posing serious health problems. Rapid and accurate detection along with timely isolation is the key to control the epidemic. Nucleic acid test and antibody-detection have been applied in the diagnosis of COVID-19, while both have their limitations. Comparatively, direct detection of viral antigens in clinical specimens is highly valuable for the early diagnosis of SARS-CoV-2. The nucleocapsid (N) protein is one of the predominantly expressed proteins with high immunogenicity during the early stages of infection. Here, we applied multiple bioinformatics servers to forecast the potential immunodominant regions derived from the N protein of SARS-CoV-2. Since the high homology of N protein between SARS-CoV-2 and SARS-CoV, we attempted to leverage existing SARS-CoV immunological studies to develop SARS-CoV-2 diagnostic antibodies. Finally, N

Indexed as

Amino Acid SequenceAnimalsComputational BiologyCoronavirus Nucleocapsid ProteinsCOVID-19Epitopes, B-LymphocyteEpitopes, T-LymphocyteHumansImmunodominant EpitopesMicePhosphoproteinsSARS-CoV-2Coronavirus Nucleocapsid ProteinsEpitopes, B-LymphocyteEpitopes, T-LymphocyteImmunodominant Epitopesnucleocapsid phosphoprotein, SARS-CoV-2Phosphoproteinsantigen-capture diagnosticsCOVID-19linear B-cell epitopesnucleocapsid proteinSARS-CoV-2

Identifiers

PMID33198594
PMCPMC7678408
OpenAlexW3104212086

What OpenQuestion holds

Textmetadata
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.