Improved prediction of smoking status via isoform-aware RNA-seq deep learning models

Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk factor for many diseases, and it has profound effects...

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Bibliographic Details
Main Authors:	Boueiz, A. (Author), Bowler, R. (Author), Castaldi, P.J (Author), Cho, M. (Author), Dy, J. (Author), Hersh, C. (Author), Lee, S. (Author), Masoomi, A. (Author), Silverman, E.K (Author), Wang, Z. (Author), Xu, Z. (Author), Zhao, T. (Author)
Format:	Article
Language:	English
Published:	Public Library of Science 2021
Subjects:	adult aged Aged Article biology Computational Biology deep learning Deep Learning deep neural network epidemiology exon Exons female Female gene gene expression profiling Gene Expression Profiling gene mapping genetics human Humans isoprotein male Male measurement accuracy middle aged Middle Aged Models, Statistical people by smoking status prediction procedures Protein Isoforms receiver operating characteristic RNA sequencing RNA-Seq ROC Curve smoking Smoking statistical model
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Improved prediction of smoking status via isoform-aware RNA-seq deep learning models

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