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Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies

GeroScience(2023)10.1007/s11357-023-00785-7Source: DataRank Database

Transfer learning in a biomaterial fibrosis model identifies in vivo senescence heterogeneity and contributions to vascularization and matrix production across species and diverse pathologies is a research paper published in GeroScience (2023). On theSindex it has a DataRank of 0. It has been cited 66 times.

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Scored on demand from live citation data

Open Access66 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (19 grants)Impact (FWCI 9.49)OA: bronzeTopics (35)IDs (PubMed, PMC, 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 (26)

James I. Andorko ORCID,Kavita Krishnan ORCID,Joscelyn C. Mejías ORCID,Helen Nguyễn ORCID,Katlin B. Stivers ORCID

Live enrichment

PubMed:37079217 PMC:PMC10651581 OpenAlex:https://openalex.org/W4366462717

U.S. Department of Defense

Grant: W81XWH-17-1-0627

U.S. Department of Defense

Grant: W81XWH-14-1-0285

Office of Strategic Coordination

Grant: DP1AR076959

National Cancer Institute

Grant: U01CA253403

Foundation for the National Institutes of Health

Grant: R01 AG057493

Foundation for the National Institutes of Health

Grant: 1T32AG058527-01

Translational Aging Research Training Program

Foundation for the National Institutes of Health

Grant: 5T32CA153952-08

T32: Predoctoral and Postdoctoral Training Program in Nanotechnology for Cancer Research

National Science Foundation

Grant: DGE-1746891

NIA NIH HHS

Grant: T32 AG058527

NIGMS NIH HHS

Grant: T32 GM136577

NIA NIH HHS

Grant: U54 AG079779

NCI NIH HHS

Grant: T32 CA153952

National Institutes of Health

Grant: 1U01CA253403-01

Single-cell and imaging data integration software to spatially resolve the tumor microenvironment

National Institutes of Health

Grant: 5R01AG057493-05

Cellular senescence in aging and age-related disease.

National Science Foundation

Grant: 1746891

Graduate Research Fellowship Program (GRFP)

National Institutes of Health

Grant: 5DP1AR076959-02

Biomaterials-directed regenerative immunotherapies

Johns Hopkins University

Bloomberg~Kimmel Institute for Cancer Immunotherapy, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University

Bristol-Myers Squibb

FWCI

9.49

Citation Percentile

1.0%

Citation Trend

2022

2023

2024

2025

2026

bronzeLicense: Springer Nature TDM

journalhttps://link.springer.com/content/pdf/10.1007/s11357-023-00785-7.pdf

publisherhttps://link.springer.com/content/pdf/10.1007/s11357-023-00785-7.pdf

publisherhttps://link.springer.com/article/10.1007/s11357-023-00785-7/fulltext.html

journalhttps://doi.org/10.1007/s11357-023-00785-7

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37079217

Fields of Study

Telomeres, Telomerase, and SenescenceSingle-cell and spatial transcriptomicsPlanarian Biology and Electrostimulation0301 basic medicine03 medical and health sciences

MeSH Terms

Machine LearningAgingAnimalsFibroblastsHumansPhenotypeCellular SenescenceMice

Keywords

SenescenceIn vivoFibrosisPhenotypeCell biologyWound healingBiologyPathologyCancer researchNeuroscienceMedicineImmunologyGeneGeneticsRna SequencingMachine LearningMiceAgingHumansAnimalsFibroblastsCellular Senescence

Sustainable Development Goals

SDG 0: Life in Land