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A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy

Cell Reports Methods(2023)10.1016/j.crmeth.2023.100546Source: DataRank Database

A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy is a research paper published in Cell Reports Methods (2023). On theSindex it has a DataRank of 0.292. It has been cited 6 times.

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0.292DataRank · unranked

Scored on demand from live citation data

Open Access6 citations

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Linked data & code

nct doi

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (9 grants)Impact (FWCI 0.55)OA: goldTopics (33)IDs (PubMed, PMC, OpenAlex)Annotations (2)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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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.292

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (8)

Jasme Lee ORCID,Matthew Adamow ORCID,Colleen Maher ORCID,Michael A. Postow ORCID,Margaret K. Callahan ORCID

Live enrichment

PubMed:37671017 PMC:PMC10475788 OpenAlex:https://openalex.org/W4385484142

NCI

Grant: R01 CA276286

NCI

Grant: P30 CA008748

National Institutes of Health

Grant: 2P30CA008748-43

MOUSE GENETICS

National Institutes of Health

Grant: 5R01CA276286-03

Understanding Immunotype, a Novel Biomarker for Checkpoint Blockade Resistance

V Foundation for Cancer Research

Bristol-Myers Squibb

National Institutes of Health

Parker Institute for Cancer Immunotherapy

AstraZeneca

FWCI

0.55

Citation Percentile

0.6%

Citation Trend

2024

2025

2026

goldLicense: cc-by-nc-nd

journalhttps://doi.org/10.1016/j.crmeth.2023.100546

GOLDhttps://doi.org/10.1016/j.crmeth.2023.100546

publisherhttps://doi.org/10.1016/j.crmeth.2023.100546

publisherhttps://api.elsevier.com/content/article/PII:S2667237523001832?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2667237523001832?httpAccept=text/plain

Fields of Study

Single-cell and spatial transcriptomicsCancer Immunotherapy and BiomarkersImmune cells in cancerMedicineBiologyComputer Science

MeSH Terms

Data AnalysisFlow CytometryHumansImmunotherapyNeoplasmsT-LymphocytesData Mining

Keywords

Flow cytometryLatent Dirichlet allocationImmune systemPeripheral bloodImmunotherapyPopulationT cellImmunologyComputational biologyComputer scienceTopic modelBiologyMedicineInformation retrievalData AnalysisT-LymphocytesNeoplasmsHumansData MiningArticle

Sustainable Development Goals

SDG 0: Good health and well-being

A topic modeling approach reveals the dynamic T cell composition of peripheral blood during cancer immunotherapy

FAIR Checklist

DataRank Breakdown

Authors (8)

Funding (9 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)