Evidence map›Paper›PMID 34497604›Full record

ArticleFrontiers in immunology

Revelation of Potent Epitopes Present in Unannotated ORF Antigens of SARS-CoV-2 for Epitope-Based Polyvalent Vaccine Design Using Immunoinformatics Approach.

Patil Pranita Uttamrao, Chakkarai Sathyaseelan, L Ponoop Prasad Patro, Thenmalarchelvi Rathinavelan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

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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 1 institution in 1 country.

Patil Pranita UttamraoDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, India.
Chakkarai SathyaseelanDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, India.
L Ponoop Prasad PatroDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, India.
Thenmalarchelvi RathinavelanDepartment of Biotechnology, Indian Institute of Technology Hyderabad, Kandi, India.
Indian Institute of Technology Hyderabad · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) kills thousands of people worldwide every day, thus necessitating rapid development of countermeasures. Immunoinformatics analyses carried out here in search of immunodominant regions in recently identified SARS-CoV-2 unannotated open reading frames (uORFs) have identified eight linear B-cell, one conformational B-cell, 10 CD4+ T-cell, and 12 CD8+ T-cell promising epitopes. Among them, ORF9b B-cell and T-cell epitopes are the most promising followed by M.ext and ORF3c epitopes. ORF9b

Indexed as

Amino Acid SequenceAntigens, ViralComputational BiologyCoronavirus Nucleocapsid ProteinsCOVID-19COVID-19 VaccinesDrug DesignEpitope MappingEpitopes, B-LymphocyteEpitopes, T-LymphocyteHumansOpen Reading FramesSARS-CoV-2Sequence Analysis, ProteinVaccines, CombinedAntigens, ViralCoronavirus Nucleocapsid ProteinsCOVID-19 VaccinesEpitopes, B-LymphocyteEpitopes, T-LymphocyteVaccines, CombinedB-cell epitopesCanonical protein epitopesepitope-based polyvalent vaccineHLA I supergroupsORF9bSARS-CoV-2T-cell epitopesuORFs

Identifiers

PMID34497604
PMCPMC8419283
OpenAlexW3196052776

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.