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Updated: May 20, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
Integrative analysis of common neurodegenerative diseases using gene association, interaction networks and mRNA
Yu Liu1, Mehmet Koyutürk, Sean Maxwell
1Center for Proteomics and Bioinformatics, Cleveland, OH.
Abstract:
Alzheimer's and Parkinson's diseases (AD and PD) are two common neurodegenerative diseases primarily affecting memory and motor functions, respectively. In this study, we integrated data from various sources, and took a systems-biology approach to compare and contrast the molecular and network based dysregulation associated with AD and PD and we integrated these data with known pathways of drug treatment. First, we identified genes that exhibit consistent prior evidence of association with each disease. Then, we extracted disease-specific sub-networks from a human interactome database using associated genes as seeds. To rank the sub-networks we used existing gene expression data from cases and controls. Comparison of resulting disease-associated genes and networks revealed significant overlap between AD and PD. In addition, the identified sub-networks correlated with known drug interdiction pathways, and suggested new potential targets for intervention.
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