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Optimizing the design of spatial genomic studies

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.01.29.526115Source: DataRank Database

Optimizing the design of spatial genomic studies is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 1 time.

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0DataRank · unranked

Scored on demand from live citation data

Open Access1 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)OA: greenTopics (7)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 (4)

Diana Cai ORCID,Didong Li ORCID,Barbara E. Engelhardt ORCID,Andrew Jones ORCID

Live enrichment

PubMed:36778332 OpenAlex:https://openalex.org/W4318679797

NIEHS NIH HHS

Grant: P30 ES010126

NCI NIH HHS

Grant: U2C CA233195

greenLicense: cc-by-nd

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/01/31/2023.01.29.526115.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.01.29.526115

repositoryhttps://doi.org/10.1101/2023.01.29.526115

repositoryhttps://pubmed.ncbi.nlm.nih.gov/36778332

Fields of Study

Single-cell and spatial transcriptomicsGene expression and cancer classificationMolecular Biology Techniques and Applications

Keywords

Computer scienceComputational biologyData scienceBiology

Sustainable Development Goals

SDG 0: Decent work and economic growth