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An interpretable Bayesian clustering approach with feature selection for analyzing spatially resolved transcriptomics data

Biometrics(2024)10.1093/biomtc/ujae066Source: DataRank Database

An interpretable Bayesian clustering approach with feature selection for analyzing spatially resolved transcriptomics data is a research paper published in Biometrics (2024). On theSindex it has a DataRank of 0. It has been cited 6 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access6 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (13 grants)Impact (FWCI 0.96)OA: greenTopics (31)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)

Bencong Zhu,Xi Jiang ORCID,Lei Guo ORCID,Yang Xie ORCID,Lin Xu ORCID

Live enrichment

PubMed:39073775 OpenAlex:https://openalex.org/W4401157960

National Science Foundation

Grant: 2210912

National Science Foundation

Grant: 2113674

National Institutes of Health

Grant: 1R01GM141519

National Institutes of Health

Grant: R01DK127037

National Institutes of Health

Grant: R01CA263079

National Institutes of Health

Grant: R21CA259771

National Institutes of Health

Grant: UM1HG011996

National Institutes of Health

Grant: R01HL144969