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Advances in omics data for eosinophilic esophagitis: moving towards multi-omics analyses

Journal of Gastroenterology(2024)10.1007/s00535-024-02151-6Source: DataRank Database

Advances in omics data for eosinophilic esophagitis: moving towards multi-omics analyses is a research paper published in Journal of Gastroenterology (2024). On theSindex it has a DataRank of 0. It has been cited 12 times.

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Open Access12 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (5 grants)Impact (FWCI 5.23)OA: hybridTopics (33)IDs (PubMed, PMC, OpenAlex)

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 (5)

Shingo Yamada ORCID,Hironori Sato ORCID,Justin Zhan ORCID,Tetsuo Shoda ORCID,Kazuhiro Matsuyama

Live enrichment

PubMed:39297956 PMC:PMC11496339 OpenAlex:https://openalex.org/W4402620918

National Institutes of Health

Grant: K99/R00 AI158660

Digestive Health Center Pilot and Feasibility Program

Grant: P30 DK078392

NIAID NIH HHS

Grant: R00 AI158660

NIAID NIH HHS

Grant: K99 AI158660

Cincinnati Children's Trustee Award

FWCI

5.23

Citation Percentile

1.0%

Citation Trend

2025

2026

hybridLicense: cc-by

journalhttps://link.springer.com/content/pdf/10.1007/s00535-024-02151-6.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/s00535-024-02151-6.pdf

publisherhttps://link.springer.com/article/10.1007/s00535-024-02151-6/fulltext.html

journalhttps://doi.org/10.1007/s00535-024-02151-6

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39297956

Fields of Study

Eosinophilic EsophagitisEosinophilic Disorders and SyndromesIL-33, ST2, and ILC Pathways

MeSH Terms

Machine LearningMultiomicsHumansQuality of LifeBiomarkersGene Expression ProfilingGenomicsProteomicsEpigenesis, GeneticEosinophilic EsophagitisTranscriptome

Keywords

Eosinophilic esophagitisOmicsEpigenomicsGenomicsProteomicsEpigeneticsDiseaseComputational biologyBioinformaticsBiologyDNA methylationMedicineGenomeGeneGeneticsGene expressionPathologyMachine LearningMulti-omics