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A supervised Bayesian factor model for the identification of multi-omics signatures

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.01.25.525545Source: DataRank Database

A supervised Bayesian factor model for the identification of multi-omics signatures 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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Open Access1 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (27)IDs (PubMed, OpenAlex)SDGs (2)

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (6)

Anna Konstorum ORCID,Shrikant Pawar ORCID,E Aron ORCID,Steven H. Kleinstein ORCID,Leying Guan ORCID

Live enrichment

PubMed:36747790 OpenAlex:https://openalex.org/W4318184372

National Institutes of Health

Grant: 5U19AI089992-08

Systems Immune Profiling of Divergent Responses to Infection

National Science Foundation

Grant: 2310836

Robust Classification and uncertainty quantification for non-iid samples

NIAID NIH HHS

Grant: U01 AI150753

greenLicense: CC BY

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/01/26/2023.01.25.525545.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.01.25.525545

repositoryhttp://dx.doi.org/10.1101/2023.01.25.525545

repositoryhttps://pubmed.ncbi.nlm.nih.gov/36747790

Fields of Study

Bioinformatics and Genomic NetworksGene expression and cancer classificationSingle-cell and spatial transcriptomics0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

OmicsProfiling (computer programming)Dimensionality reductionComputer scienceMachine learningComputational biologyBiomarker discoveryIdentification (biology)Bayesian probabilityArtificial intelligenceData miningBioinformaticsBiologyProteomicsGeneOriginal PaperHumansBayes TheoremGenomicsSupervised Machine LearningMultiomics

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being