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Cell population‐based framework of genetic epidemiology in the single‐cell omics era

BioEssays(2022)10.1002/bies.202100118Source: DataRank Database

Cell population‐based framework of genetic epidemiology in the single‐cell omics era is a research paper published in BioEssays (2022). On theSindex it has a DataRank of 0.457. It has been cited 20 times.

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0.457DataRank · unranked

Scored on demand from live citation data

20 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)Impact (FWCI 1.82)OA: hybridTopics (29)Linked Datasets (18)DataCite Reuse (18)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (0/2)

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.457

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

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Authors (4)

Cheng Zheng ORCID,Jian Hao Cheng,Ryo Yamada,Daigo Okada ORCID

Live enrichment

PubMed:34821401 OpenAlex:https://openalex.org/W3217628151

Japan Science and Technology Agency

Grant: AIP Challenge 2020

Japan Science and Technology Agency

Grant: JPMJCR21U2

Japan Society for the Promotion of Science

Grant: JP19J14816

Japan Society for the Promotion of Science

Grant: 21K21316

Core Research for Evolutional Science and Technology

Grant: JPMJCR1502

Core Research for Evolutional Science and Technology

Grant: JPMJCR15G1

FWCI

1.82

Citation Percentile

0.9%

Citation Trend

2022

2023

2024

2025

hybridLicense: cc-by

journalhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/bies.202100118

publisherhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/bies.202100118

publisherhttps://onlinelibrary.wiley.com/doi/pdf/10.1002/bies.202100118

publisherhttps://onlinelibrary.wiley.com/doi/full-xml/10.1002/bies.202100118

journalhttps://doi.org/10.1002/bies.202100118

Fields of Study

Single-cell and spatial transcriptomicsGene Regulatory Network AnalysisBioinformatics and Genomic NetworksEpidemiological ModelsGenomicsMolecular EpidemiologySystems BiologyTranscriptome

MeSH Terms

Epidemiological ModelsMolecular EpidemiologyGenomicsSystems BiologyTranscriptome

Keywords

PopulationComputational biologyGenetic epidemiologyOmicsBiologyComputer scienceBioinformaticsGeneticsMedicineGeneSingle cellGenomicsTranscriptomesystems biologyEpigenomeGwas

Sustainable Development Goals

SDG 0: Good health and well-being

Additional file 1 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568031.v1figshare

Additional file 1 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568031figshare

Additional file 2 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568034.v1figshare

Additional file 2 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568034figshare

Additional file 5 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568043.v1figshare

Additional file 5 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568043figshare

Additional file 6 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568046.v1figshare

Additional file 6 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568046figshare

Additional file 7 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568049.v1figshare

Additional file 7 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568049figshare

Additional file 8 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568052.v1figshare

Additional file 8 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568052figshare

Additional file 9 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568055.v1figshare

Additional file 9 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568055figshare

Additional file 3 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568037.v1figshare

Additional file 4 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568040.v1figshare

Additional file 4 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568040figshare

Additional file 3 of Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

10.6084/m9.figshare.26568037figshare

Cell population‐based framework of genetic epidemiology in the single‐cell omics era

FAIR Checklist

DataRank Breakdown

Authors (4)

Funding (6 grants)

Impact

Open Access

Topics

Linked Datasets (18)