Fused multi-modal similarity network as prior in guiding brain imaging genetic association.

Deciphering the tissue-specific functional effect of Alzheimer risk SNPs with deep genome annotation.

Deep learning-based identification of genetic variants: application to Alzheimer's disease classification.

Integrative-omics for discovery of network-level disease biomarkers: a case study in Alzheimer's disease.

Brain-wide structural connectivity alterations under the control of Alzheimer risk genes.

Deep learning detection of informative features in tau PET for Alzheimer's disease classification.

Deep Learning in Alzheimer's disease: Diagnostic Classification and Prognostic Prediction using Neuroimaging Data.

Longitudinal Genotype-Phenotype Association Study through Temporal Structure Auto-Learning Predictive Model.

Quantitative trait loci identification for brain endophenotypes via new additive model with random networks.

Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer's disease.

Two-dimensional enrichment analysis for mining high-level imaging genetic associations.

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules.

From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs.

Identifying quantitative trait loci via group-sparse multitask regression and feature selection: an imaging genetics study of the ADNI cohort.

Whole genome association study of brain-wide imaging phenotypes for identifying quantitative trait loci in MCI and AD: A study of the ADNI cohort.