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Multi-omic modeling of antidepressant response implicates dynamic immune and inflammatory changes in individuals who respond to treatment.

Shih-Chieh FuhLaura M FioriGustavo TureckiCorina NagyYue Li
Published in: PloS one (2023)
The derived meta-phenotypes and associated biological functions represent both biomarkers to predict response, as well as potential new treatment targets. Our method is applicable to other diseases with multi-omic data, and the software is open source and available on Github (https://github.com/li-lab-mcgill/iGEM).
Keyphrases
  • oxidative stress
  • combination therapy
  • data analysis
  • electronic health record
  • machine learning
  • risk assessment