Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

A transcriptome-informed QSP model of metastatic triple-negative breast cancer identifies predictive biomarkers for PD-1 inhibition

Science Advances(2023)10.1126/sciadv.adg0289Source: DataRank Database

A transcriptome-informed QSP model of metastatic triple-negative breast cancer identifies predictive biomarkers for PD-1 inhibition is a research paper published in Science Advances (2023). On theSindex it has a DataRank of 0. It has been cited 29 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access29 citations

Download PDF

Cite:

Linked data & code

geo doi

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 3.38)OA: goldTopics (36)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)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (5)

Hanwen Wang ORCID,Leisha A. Emens ORCID,Cesar A. Santa‐Maria ORCID,Aleksander S. Popel ORCID,Theinmozhi Arulraj ORCID

Live enrichment

PubMed:37390206 PMC:PMC10313177 OpenAlex:https://openalex.org/W4382753177

National Institutes of Health

Grant: 5R01LM013039-02

HealthyMe/MiSalud Smartphone Application: Identifying Mechanisms to Engage African Americans and Hispanics in Personal Health Libraries

National Institutes of Health

Grant: 5U01CA212007-03

Integrating bioinformatics into multiscale models for hepatocellular carcinoma

National Science Foundation

Grant: 1920103

MRI: Acquisition of an Advanced Computing Instrument to Integrate Data-Driven Research and Data intensive computing at Johns Hopkins University

National Institutes of Health

Grant: 5R01CA138264-13

Predictive experiment-based multiscale models of the tumor immune microenvironment and immunotherapy in breast cancer

FWCI

3.38

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://www.science.org/doi/pdf/10.1126/sciadv.adg0289?download=true

publisherhttps://www.science.org/doi/pdf/10.1126/sciadv.adg0289?download=true

publisherhttps://www.science.org/doi/pdf/10.1126/sciadv.adg0289

journalhttps://doi.org/10.1126/sciadv.adg0289

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37390206

Fields of Study

Cancer Immunotherapy and BiomarkersFerroptosis and cancer prognosisCancer Genomics and Diagnostics03 medical and health sciences0302 clinical medicine

MeSH Terms

Antigen-Presenting CellsHumansLymph NodesBiomarkersTranscriptomeTriple Negative Breast Neoplasms

Keywords

Triple-negative breast cancerBreast cancerPembrolizumabCancerMedicineMetastatic breast cancerTranscriptomeIn silicoOncologyBiomarkerCancer researchClinical trialCytotoxic T cellInternal medicineImmunotherapyBiologyGene expressionGeneIn vitroHumansAntigen-Presenting CellsTriple Negative Breast NeoplasmsBiomedicine and Life SciencesLymph NodesBiomarkers

Sustainable Development Goals

SDG 0: Good health and well-being