The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches

The feasibility of developing biomarkers from peripheral blood mononuclear cell RNAseq data in children with juvenile idiopathic arthritis using machine learning approaches

Abstract Background The response to treatment for juvenile idiopathic arthritis (JIA) can be staged using clinical features. However, objective laboratory biomarkers of remission are still lacking. In this study, we used machine learning to predict JIA activity from transcriptomes from peripheral bl...

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Bibliographic Details
Main Authors: Kerry E. Poppenberg, Kaiyu Jiang, Lu Li, Yijun Sun, Hui Meng, Carol A. Wallace, Teresa Hennon, James N. Jarvis
Format: Article
Language:English
Published: BMC 2019-11-01
Series:Arthritis Research & Therapy
Subjects:
Juvenile idiopathic arthritis
Peripheral blood mononuclear cells
Transcriptome
Machine learning
Online Access:http://link.springer.com/article/10.1186/s13075-019-2010-z

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http://link.springer.com/article/10.1186/s13075-019-2010-z

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