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

Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity

(2022)10.3389/fgene.2021.785436Source: DataRank Database

Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity is a research paper (2022). On theSindex it has a DataRank of 0. It has been cited 10 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access10 citations

Download PDF

Cite:

Linked data & code

refsnp

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 (6 grants)Impact (FWCI 1.68)OA: goldTopics (25)IDs (PubMed, PMC, OpenAlex)Annotations (1)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)

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 (6)

William Schierding ORCID,Sophie Farrow ORCID,Antony A. Cooper ORCID,Andreas W. Kempa-Liehr ORCID,Justin M. O’Sullivan ORCID

Live enrichment

PubMed:35047012 PMC:PMC8762216 OpenAlex:https://openalex.org/W4225944174

Wellcome Trust

Grant: 090355

WTCCC3 core activities.

Wellcome Trust

Grant: 076113

The genetics of weight, BMI, adiposity and obesity

Wellcome Trust

Grant: 085475

WTCCC2 core activities

Wellcome Trust

Michael J. Fox Foundation for Parkinson’s Research

Ministry for Business Innovation and Employment

FWCI

1.68

Citation Percentile

0.8%

Citation Trend

2022

2023

2024

2025

goldLicense: cc-by

journalhttps://doi.org/10.3389/fgene.2021.785436

publisherhttps://doi.org/10.3389/fgene.2021.785436

publisherhttps://www.frontiersin.org/articles/10.3389/fgene.2021.785436/full

repositoryhttps://pubmed.ncbi.nlm.nih.gov/35047012

repositoryhttps://doaj.org/article/1baa78bf6e904c66ab792fe373977d8e

Fields of Study

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and AnimalsParkinson's Disease Mechanisms and Treatments0301 basic medicine03 medical and health sciences

Keywords

Expression quantitative trait lociGenome-wide association studyBiologySingle-nucleotide polymorphismGenetic associationGeneticsQuantitative trait locusBioinformaticsComputational biologyGeneGenotypeParkinson’s DiseaseGbaSncaMachine LeaningBrain CerebellumHeart Atrial AppendagePd-SnpsTissue Specific EqtlQH426-470

Sustainable Development Goals

SDG 3: 3. Good health

Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity

FAIR Checklist

Authors (6)

Funding (6 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)