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REDIAL-2020: A suite of machine learning models to estimate Anti-SARS-CoV-2 activities

PubMed(2020)10.21203/rs.3.rs-76894/v1Source: DataRank Database

REDIAL-2020: A suite of machine learning models to estimate Anti-SARS-CoV-2 activities is a research paper published in PubMed (2020). On theSindex it has a DataRank of 0. It has been cited 6 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access6 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)OA: goldTopics (15)IDs (PubMed, OpenAlex)SDGs (2)

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)

Giovanni Bocci ORCID,Srijan Verma,Md. Rakibul Hassan ORCID,Jayme Holmes ORCID,Jeremy J. Yang ORCID

Live enrichment

PubMed:33200119 OpenAlex:https://openalex.org/W3102359187

National Institutes of Health

Grant: 5U24CA224370-06

Knowledge Management Center for Illuminating the Druggable Genome

National Science Foundation

Grant: 1827745

PREM Center for Energy and Biomaterials

goldLicense: cc-by

https://www.researchsquare.com/article/rs-76894/latest.pdf

publisherhttps://www.researchsquare.com/article/rs-76894/v1

publisherhttps://www.researchsquare.com/article/rs-76894/v1.html

https://doi.org/10.21203/rs.3.rs-76894/v1

Fields of Study

COVID-19 diagnosis using AISARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research Studies

Keywords

SuiteCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakComputer scienceVirologyArtificial intelligenceBiologyMedicineGeographyInfectious disease (medical specialty)Article

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being