Machine learning approaches to predict lupus disease activity from gene expression data

The integration of gene expression data to predict systemic lupus erythematosus (SLE) disease activity is a significant challenge because of the high degree of heterogeneity among patients and study cohorts, especially those collected on different microarray platforms. Here we deployed machine learn...

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Bibliographic Details
Published in:Sci Rep
Main Authors: Kegerreis, Brian, Catalina, Michelle D., Bachali, Prathyusha, Geraci, Nicholas S., Labonte, Adam C., Zeng, Chen, Stearrett, Nathaniel, Crandall, Keith A., Lipsky, Peter E., Grammer, Amrie C.
Format: Artigo
Language:Inglês
Published: Nature Publishing Group UK 2019
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Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC6610624/
https://ncbi.nlm.nih.gov/pubmed/31270349
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-45989-0
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