Predictive modeling of drug-induced gene expressions is a powerful tool for phenotype-
based compound screening and drug repurposing. State-of-the-art machine learning …

Mitochondrial dysfunction is an early and prominent feature of Alzheimer's disease (AD),
with impaired energy metabolism preceding the onset of clinical symptoms. Here we …

Protein inhibitor of activated STAT1 (PIAS1), a small ubiquitin-like modifier (SUMO) E3
ligase, was considered to be an inhibitor of STAT1 by inhibiting the DNA-binding activity of …

With the evolution of multicellularity, communication among cells in different tissues and
organs became pivotal to life. Molecular basis of such communication has long been …

Biomedical research studies have generated large multi-omic datasets to study complex
diseases like Alzheimer's disease (AD). An important aim of these studies is the …

Background Alzheimer's disease (AD) is neuropathologically characterized by amyloid-beta
(Aβ) plaques and neurofibrillary tangles. The main protein components of these hallmarks …

Fig. 2 Single-cell analysis.(A) Cell annotation;(B) Violin plots of cell marker expression;(C)
Difference in SLC30A9 related gene scores between two groups;(D) Difference in SLC30A9 …

Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing
irreversible brain damage to the elderly and presents a major public health challenge …

Objective: We describe herein a bioinformatics approach that leverages gene expression
data from brain homogenates to derive cell-type specific differential expression results …

State-of-the-art rare variant association testing methods aggregate the contribution of rare
variants in biologically relevant genomic regions to boost statistical power. However, testing …