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15 March 2019 Extraction of co-expressed discriminative features of schizophrenia in imaging epigenetics framework
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Abstract
Integration of imaging and non-imaging data has been a heated topic in biomedicine. While functional magnetic resonance imaging (fMRI) can serve as endo-phenotype for mental disorders, many recent researches have confirmed the essential role played by epigenetic factors in the progress of various mental diseases including Schizophrenia(SZ), which fosters an emerging branch imaging epigenetics. In this study, we focus on the integration of fMRI and DNA methylation to have a deeper understanding of SZ: we applied a model combining Lasso with Canonical Correlation Analysis (CCA) for joint DNA methylation and fMRI analysis of 184 subjects (80 patients,104 healthy controls). In the model, the regression term focuses on extracting the discriminative features associated with the disease, while the CCA term incorporates the co-expression among extracted features.We succeeded in
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© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuntong Bai, Zille Pascal, Vince D. Calhoun, and Yu-Ping Wang "Extraction of co-expressed discriminative features of schizophrenia in imaging epigenetics framework", Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109530X (15 March 2019); https://doi.org/10.1117/12.2513024
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