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Quantifying Cell-State Densities in Single-Cell Phenotypic Landscapes using Mellon

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.07.09.548272Source: DataRank Database

Quantifying Cell-State Densities in Single-Cell Phenotypic Landscapes using Mellon is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 7 times.

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Open Access7 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (2 grants)OA: greenTopics (22)IDs (PubMed, OpenAlex)

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Authors (5)

C. Diana Jordan ORCID,Brennan Dury ORCID,Christine Dien ORCID,Manu Setty ORCID,Dominik J. Otto ORCID

Live enrichment

PubMed:37502954 OpenAlex:https://openalex.org/W4383874578

National Institutes of Health

Grant: 1S10OD028685-01

High-Performance Compute Cluster for Comprehensive Cancer and Infectious Diseases Research

National Institutes of Health

Grant: 5R35GM147125-03

Computational Modeling of Lineage Decisions using Single-cell Data

greenLicense: cc-by

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/07/11/2023.07.09.548272.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.07.09.548272

repositoryhttps://doi.org/10.1101/2023.07.09.548272

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37502954

Fields of Study

Single-cell and spatial transcriptomicsCell Image Analysis TechniquesAdvanced Fluorescence Microscopy Techniques0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

PhenotypeCellState (computer science)Computer scienceBiologyGeneticsGeneAlgorithmMiceAnimalsHumansCell DifferentiationCell CountSingle-Cell AnalysisArticleAlgorithms