The finely tuned regulation of neuronal firing relies on the integrity of ion channel
macromolecular complexes. Minimal disturbances of these tightly regulated networks can …

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being
used in dementia research. However, several methodological challenges exist that may limit …

Background Genotypes are strongly associated with disease phenotypes, particularly in
brain disorders. However, the molecular and cellular mechanisms behind this association …

A novel non-parallel hyperplane Universum support vector machine (U-NHSVM) is
proposed in this paper. Universum data with ensconced prior knowledge are exploited by a …

In the past decade, multimodal neuroimaging and genomic techniques have been
increasingly developed. As an interdisciplinary topic, brain imaging genomics is devoted to …

Alzheimer's disease (AD) is a neurodegenerative disease in which genetic factors contribute
approximately 70% of etiological effects. Studies have found many significant genetic and …

While considerable advances have been made in estimating high-dimensional structured
models from independent data using Lasso-type models, limited progress has been made …

Abstract Alzheimer's disease (AD), acknowledged as the most common progressive
neurodegenerative disorder, is the leading cause of dementia in the elderly. The …

Increasingly amounts of biological data promote the development of various penalized
regression models. This review discusses the recent advances in both linear and logistic …

Abstract Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used
approach for the generation of gene co-expression networks. However, networks generated …