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19 p, 5.8 MB Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction / Iborra Egea, Oriol (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Gálvez-Montón, Carolina (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Prat-Vidal, Cristina (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Rudilla, F (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Soler-Botija, Carolina (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Revuelta-López, Elena (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Ferrer-Curriu, Gemma (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Segú-Vergés, Cristina (Anaxomics Biotech S.L.) ; Mellado-Bergillos, Araceli (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Gomez-Puchades, Pol (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Gastelurrutia, Paloma (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Bayés-Genís, Antoni (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol) ; Universitat Autònoma de Barcelona
Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. [...]
2021 - 10.3390/cells10123268
Cells, Vol. 10 (november 2021)  
Detailed record - Creative Commons

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