Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease

BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learning approach. METHODS: At the transcriptomic level,...

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Detalles Bibliográficos
Autores principales: Liu, Yaozhong, Bai, Fan, Tang, Zhenwei, Liu, Na, Liu, Qiming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842070/
https://www.ncbi.nlm.nih.gov/pubmed/33509101
http://dx.doi.org/10.1186/s12872-020-01819-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7842070/
https://www.ncbi.nlm.nih.gov/pubmed/33509101
http://dx.doi.org/10.1186/s12872-020-01819-0

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