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Riboformer: A Deep Learning Framework for Predicting Context-Dependent Translation Dynamics

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.04.24.538053Source: DataRank Database

Riboformer: A Deep Learning Framework for Predicting Context-Dependent Translation Dynamics is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 4 times.

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0DataRank · unranked

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Open Access4 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (1 grants)OA: greenTopics (19)IDs (PubMed, OpenAlex)

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 (4)

Jiawei Yan ORCID,Jing Zhang ORCID,Allen R. Buskirk ORCID,Bin Shao ORCID

Live enrichment

PubMed:37163112 OpenAlex:https://openalex.org/W4367302953

National Institutes of Health

Grant: 5R01GM136960-02

The role of collisions in rescuing stalled ribosomes in bacteria

greenLicense: cc-by-nc

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/04/28/2023.04.24.538053.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.04.24.538053

repositoryhttps://doi.org/10.1101/2023.04.24.538053

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37163112

Fields of Study

RNA and protein synthesis mechanismsRNA modifications and cancerRNA Research and Splicing0206 medical engineering02 engineering and technology

Keywords

Ribosome profilingTranslation (biology)Computational biologyProteostasisIn silicoBiologyRibosomeComputer scienceTranslational regulationGeneticsMessenger RNAGeneRNAArticle