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Cell State Transition Models Stratify Breast Cancer Cell Phenotypes and Reveal New Therapeutic Targets

Cancers(2024)10.3390/cancers16132354Source: DataRank Database

Cell State Transition Models Stratify Breast Cancer Cell Phenotypes and Reveal New Therapeutic Targets is a research paper published in Cancers (2024). On theSindex it has a DataRank of 0. It has been cited 3 times.

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Open Access3 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (9 grants)Impact (FWCI 0.64)OA: goldTopics (27)IDs (PubMed, PMC, OpenAlex)Annotations (1)SDGs (2)

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 (8)

Hiroaki Imoto ORCID,Ayush Tambde,Amy McGillycuddy,Philipp Junk ORCID,Anna Tuliakova ORCID

Live enrichment

PubMed:39001416 PMC:PMC11240448 OpenAlex:https://openalex.org/W4400090373

NIH

Grant: R01CA244660

NIH

Grant: 101136926 MULTIR

NIH

Grant: 22/PATH-S/10875

Using cyber-physical network modelling to tackle RAS-driven cancers

NIH

Grant: 18/RI/5702

A national platform for comprehensive molecular analysis underpinning chemistry, the bioeconomy, and precision oncology research: from molecules to microorganisms and humans.

NIH

Grant: 18/SPP/3522

Precision Oncology Ireland

NIH

Grant: 22/FFP-A/10729

The Role of Dynamic Protein-Protein Interaction Changes in Adaptive Drug Resistance

JSPS Overseas Research

Grant: Fellowships

National Institutes of Health

Grant: 5R01CA244660-03

Multiscale Modeling to Optimize Inhibition of Oncogenic ERK Pathway Signaling

European Commission

Grant: 101136926

MULti-Tumour based prediction and manipulation of Immune Response

FWCI

0.64

Citation Percentile

0.7%

Citation Trend

2025

2026

goldLicense: cc-by

journalhttps://doi.org/10.3390/cancers16132354

publisherhttps://doi.org/10.3390/cancers16132354

publisherhttps://www.mdpi.com/2072-6694/16/13/2354/pdf

repositoryhttps://pubmed.ncbi.nlm.nih.gov/39001416

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/11240448

Fields of Study

Gene Regulatory Network AnalysisBioinformatics and Genomic NetworksSingle-cell and spatial transcriptomics0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

BiologyPhenotypeCellComputational biologyBreast cancerCell cultureCell signalingSystems biologySignal transductionCancer researchCell biologyCancerGeneticsGeneMachine LearningNetwork ReconstructionMathematical ModelingSignaling NetworksDigital TwinsCstarArticle

Sustainable Development Goals

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

Cell State Transition Models Stratify Breast Cancer Cell Phenotypes and Reveal New Therapeutic Targets

FAIR Checklist

Authors (8)

Funding (9 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)