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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.5281/zenodo...
Dataset . 2023
License: CC BY
Data sources: Sygma
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Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease

Authors: Ramirez Flores, Ricardo Omar; Lanzer, Jan David; Dimitrov, Daniel; Velten, Britta; Saez-Rodriguez, Julio;

Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease

Abstract

Collection of auxiliary data to reproduce the results from "Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease". Source code is available at: https://github.com/saezlab/MOFAcell Exceptions: Spatial data is excluded This folder contains processed data of the following publications, when using the data cite accordingly: 1) Kuppe C, Ramirez Flores RO, Li Z, Hayat S, Levinson RT, Liao X, Hannani MT, Tanevski J, Wünnemann F, Nagai JS, et al (2022) Spatial multi-omic map of human myocardial infarction. Nature 608: 766–777 2) Ramirez Flores RO, Lanzer JD, Holland CH, Leuschner F, Most P, Schultz J-H, Levinson RT & Saez-Rodriguez J (2021) Consensus Transcriptional Landscape of Human End-Stage Heart Failure. J Am Heart Assoc 10: e019667 3) Reichart D, Lindberg EL, Maatz H, Miranda AMA, Viveiros A, Shvetsov N, Gärtner A, Nadelmann ER, Lee M, Kanemaru K, et al (2022) Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies. Science 377: eabo1984 4) Chaffin M, Papangeli I, Simonson B, Akkad A-D, Hill MC, Arduini A, Fleming SJ, Melanson M, Hayat S, Kost-Alimova M, et al (2022) Single-nucleus profiling of human dilated and hypertrophic cardiomyopathy. Nature 608: 174–180

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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
Average
Average
32
32
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