Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to redu...

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Bibliographic Details
Main Authors: Yichuan Liu, Hui-Qi Qu, Xiao Chang, Lifeng Tian, Jingchun Qu, Joseph Glessner, Patrick M. A. Sleiman, Hakon Hakonarson
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:International Journal of Molecular Sciences
Subjects:
schizophrenia
machine learning
transcriptome
long non-coding RNAs
Online Access:https://www.mdpi.com/1422-0067/22/7/3364

Internet

https://www.mdpi.com/1422-0067/22/7/3364

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