Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics

BACKGROUND: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing (WGS) data with metabolomics data has emerged as a promising approach to enhance the accuracy of data imputation in met...

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Detalles Bibliográficos
Autores principales: Zhao, Chen, Su, Kuan-Jui, Wu, Chong, Cao, Xuewei, Sha, Qiuying, Li, Wu, Luo, Zhe, Qin, Tian, Qiu, Chuan, Zhao, Lan Juan, Liu, Anqi, Jiang, Lindong, Zhang, Xiao, Shen, Hui, Zhou, Weihua, Deng, Hong-Wen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593076/
https://www.ncbi.nlm.nih.gov/pubmed/37873011

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593076/
https://www.ncbi.nlm.nih.gov/pubmed/37873011

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