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ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning

bioRxiv (Cold Spring Harbor Laboratory)(2025)10.1101/2025.07.17.665451Source: DataRank Database

ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2025). 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 (5 grants)OA: greenTopics (14)IDs (PubMed, OpenAlex)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 (7)

Weinan Zhang ORCID,Chaohan Li,Yuexu Jiang,Duolin Wang ORCID,Qing Shao ORCID

Live enrichment

PubMed:40777512 OpenAlex:https://openalex.org/W4412587518

National Institutes of Health

Grant: R35GM126985

National Institutes of Health

Grant: R01LM014510

GPU resources through allocations

Grant: NAIRR240246

GPU resources through allocations

Grant: NAIRR250134

National Artificial Intelligence Research Resource

greenLicense: cc-by-nc-nd

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2025/07/22/2025.07.17.665451.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2025.07.17.665451

repositoryhttps://doi.org/10.1101/2025.07.17.665451

repositoryhttps://pubmed.ncbi.nlm.nih.gov/40777512

Fields of Study

Machine Learning in BioinformaticsBiochemical and Structural Characterizationvaccines and immunoinformatics approaches

Keywords

Subcellular localizationProtein subcellular localization predictionComputer scienceArtificial intelligenceRobustness (evolution)Reinforcement learningBenchmark (surveying)MacroMachine learningBiologyGene

Sustainable Development Goals

SDG 0: Partnerships for the goals