Analysis of cardiac single-cell RNA-sequencing data can be improved by the use of artificial-intelligence-based tools.

Nguyen, Thanh; Wei, Yuhua; Nakada, Yuji; Chen, Jake Y; Zhou, Yang; Walcott, Gregory; Zhang, Jianyi

Nguyen, Thanh; Wei, Yuhua; Nakada, Yuji; Chen, Jake Y; Zhou, Yang; Walcott, Gregory; Zhang, Jianyi.

Afiliação

Nguyen T; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Wei Y; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Nakada Y; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Chen JY; Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Zhou Y; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Walcott G; Department of Medicine, Cardiovascular Diseases, University of Alabama at Birmingham, Birmingham, AL, 35233, USA.
Zhang J; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, 35233, USA. jayzhang@uab.edu.

Sci Rep ; 13(1): 6821, 2023 04 26.

Article em En | MEDLINE | ID: mdl-37100826

Assuntos

Inteligência Artificial; Infarto do Miocárdio; Animais; Camundongos; Humanos; Suínos; Miócitos Cardíacos/metabolismo; Infarto do Miocárdio/metabolismo; RNA/metabolismo; Inteligência

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Infarto do Miocárdio Limite: Animals / Humans Idioma: En Revista: Sci Rep Ano de publicação: 2023 Tipo de documento: Article

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