Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

A suite of designed protein cages using machine learning and protein fragment-based protocols

Structure(2024)10.1016/j.str.2024.02.017Source: DataRank Database

A suite of designed protein cages using machine learning and protein fragment-based protocols is a research paper published in Structure (2024). On theSindex it has a DataRank of 0. It has been cited 21 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access21 citations

Download PDF

Cite:

Linked data & code

pdb doi

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (8 grants)Impact (FWCI 6.64)OA: hybridTopics (35)IDs (PubMed, PMC, OpenAlex)Annotations (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)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (8)

Roger Castells‐Graells ORCID,Roman Aguirre ORCID,M.R. Sawaya ORCID,Mark A. Arbing ORCID,Trent Sherman ORCID

Live enrichment

PubMed:38513658 PMC:PMC11162342 OpenAlex:https://openalex.org/W4392976128

NIGMS NIH HHS

Grant: U24 GM129541

NIGMS NIH HHS

Grant: R01 GM129854

NIGMS NIH HHS

Grant: T32 GM008496

NIGMS NIH HHS

Grant: P30 GM124165

NIGMS NIH HHS

Grant: U24 GM129547

NIGMS NIH HHS

Grant: P30 GM133894

NIH HHS

Grant: S10 OD021512

National Institutes of Health

FWCI

6.64

Citation Percentile

1.0%

Citation Trend

2023

2024

2025

2026

hybridLicense: cc-by

journalhttp://www.cell.com/article/S096921262400056X/pdf

publisherhttp://www.cell.com/article/S096921262400056X/pdf

publisherhttps://api.elsevier.com/content/article/PII:S096921262400056X?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S096921262400056X?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.str.2024.02.017

Fields of Study

Bacteriophages and microbial interactionsMonoclonal and Polyclonal Antibodies ResearchGenomics and Phylogenetic StudiesMachine LearningProteinsHydrophobic and Hydrophilic InteractionsProtein ConformationMolecular Docking SimulationCryoelectron MicroscopyModels, Molecular

MeSH Terms

Machine LearningModels, MolecularProtein ConformationProteinsCryoelectron MicroscopyHydrophobic and Hydrophilic InteractionsMolecular Docking Simulation

Keywords

SuiteProtein designFragment (logic)Computer scienceInterface (matter)Computational biologyProtein structureBiologyBiochemistryAlgorithmSymmetryX-ray crystallographySelf-assemblyMachine LearningCryoemProtein-protein DockingProtein CagesDe Novo Interface Design

A suite of designed protein cages using machine learning and protein fragment-based protocols

FAIR Checklist

Authors (8)

Funding (8 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)