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Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.03.23.436603Source: DataRank Database

Cell-to-cell and type-to-type heterogeneity of signaling networks: Insights from the crowd is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2021). 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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Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd. · European Molecular Biology Organization

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (3 grants)OA: greenTopics (42)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, OpenAlex)SDGs (2)

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Findable (2/2)

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Accessible (1/2)

Open Access

Interoperable (2/2)

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Authors (11)

Marco Tognetti ORCID,Alice Driessen ORCID,Jovan Tanevski ORCID,Baosen Guo ORCID,Wencai Cao

Live enrichment

PubMed:19022398 OpenAlex:https://openalex.org/W3138524623

European Commission

Grant: 866074

Analysis of functional tissue motifs for precision medicine in metastatic breast cancer

National Institutes of Health

Grant: 1UC4DK108132-01

Single-Cell Analyses of Human Islets in T1D Using Highly Multiplexed Imaging

European Commission

Grant: 336921

Three Dimensional Single Cell Analysis of the Cancer Stem Cell Inducing Epithelial-Mesenchymal Transition Signaling Networks in Breast Cancer by Mass Cytometry

greenLicense: cc-by-nc

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2021/04/12/2021.03.23.436603.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2021.03.23.436603

repositoryhttps://doi.org/10.1101/2021.03.23.436603

repositoryhttps://www.repository.cam.ac.uk/handle/1810/330761

Fields of Study

Single-cell and spatial transcriptomicsCell Image Analysis TechniquesGene Regulatory Network Analysis0301 basic medicine03 medical and health sciences0303 health sciences

Keywords

Mass cytometryCell typeBiologySignal transductionComputational biologyCellComputer sciencePhenotypeCell biologyGeneticsGene570Medicine (General)BioinformaticsQH301-705.51.1 Normal biological development and functioningBreast NeoplasmsMachine LearningR5-920cell signaling; crowdsourcing; mass cytometry; predictive modeling; single cellUnderpinning researchBreast CancerHumanscell signalingBiology (General)CancerProteinsArticlessingle cellFemalecrowdsourcingGeneric health relevanceBiochemistry and Cell BiologyOther Biological SciencesSingle Cell Signaling in Breast Cancer DREAM Consortium memberspredictive modeling

Sustainable Development Goals

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

Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd.

10.17863/cam.78202European Molecular Biology Organization