Imaging Genomics based Brain Disease Prediction

Research project

Description

The goal of this project is to develop, validate and apply novel computational and system biology algorithms and tools for comprehensive joint analysis of large-scale heterogeneous imaging genomic data, with applications to early prediction of conversion of Mild Cognitive Impairment (MCI) to Alzheimer Disease (AD). UNC team will work on Aims 1 and 2 of this project, for developing a novel sparse learning based system biology framework for analysis of genome-wide association results across a large number of the structural and functional phenotypes derived from MRI and PET scans of the whole brain, as well as for developing the new structured sparsity-inducing norms based multi-dimensional data integration methods to identify the biomarkers from heterogeneous imaging genomic data for MCI conversion prediction.
StatusActive
Effective start/end date9/1/154/30/20

Funding

  • University of Texas at Arlington

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Brain
Imaging techniques
Systems Biology
Genomics
Data integration
Biomarkers
Magnetic resonance imaging
Genes
Association reactions