Incorporating spatial–anatomical similarity into the VGWAS framework for AD biomarker detection

Abstract

The detection of potential biomarkers of Alzheimer’s disease (AD) is crucial for its early prediction, diagnosis and treatment. Voxel-wise genome-wide association study (VGWAS) is a commonly used method in imaging genomics and usually applied to detect AD biomarkers in imaging and genetic data. However, existing VGWAS methods entail large computational cost and disregard spatial correlations within imaging data. A novel method is proposed to solve these issues.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 16, 2019
Source ID
10.1093/bioinformatics/btz401

Entities

People

  • Meiyan Huang
  • Qianjin Feng
  • The Alzheimer’s Disease Neuroimaging Initiative*
  • Wei Yang
  • Yuwei Yu

Organizations

  • Alzheimer's Disease Neuroimaging Initiative
  • National Institutes of Health
  • National Natural Science Foundation of China
  • Southern Medical University
  • United States Department of Defense

Tags

Readers

  • Neural Network Machine Learning.
  • Oncology
  • Traumatic Brain Injury (TBI) and Cognitive Aging in the Guam and Border Populations Affected by Alzheimer's Disease and Tau-Associated Dementias.

Technology Areas

  • Biotechnology