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In Silico Defined SARS-CoV2 Epitopes May Not Predict Immunogenicity to COVID19

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.07.08.451555Source: DataRank Database

In Silico Defined SARS-CoV2 Epitopes May Not Predict Immunogenicity to COVID19 is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2021). On theSindex it has a DataRank of 0.

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)OA: greenTopics (2)IDs (PubMed)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (8)

Yulun Chiu,Michelle Chen ORCID,Junmei Wang ORCID,Ivy Lai,Shailbala Singh ORCID

Live enrichment

PubMed:19162232

National Institutes of Health

Grant: 3P30CA016672-41S4

Cancer Center Support (CORE) Grant

National Institutes of Health

Grant: 3R01CA237672-02S1

T Cell Immunity Of COVID19: Developing Biomarker And Therapeutic Strategies

green

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2021/07/08/2021.07.08.451555.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2021.07.08.451555

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/8282092

https://doi.org/10.1101/2021.07.08.451555

https://pubmed.ncbi.nlm.nih.gov/34268504

Fields of Study

0301 basic medicine03 medical and health sciences

Sustainable Development Goals

SDG 3: 3. Good health