Abstract
Alzheimer's disease (AD) is considered one of the most common age-associated neurodegenerative disorders, affecting millions of senior people worldwide. Combination of protein–protein interaction (PPI) network analysis and gene expression studies provides a better insight into AD. A computational approach was developed in our work to identify protein signal pathways between amyloid precursor proteins and tau proteins, which are well known as important proteins for AD. First, a modified LA-SEN method, called the network-constrained regularisation analysis, was applied to microarray data from a transgenic mouse model and AD patients. Then protein pathways were constructed based on an integer linear programming model to integrate microarray data and the PPI database. Important pathways of AD, including some cancer-related pathways, were identified finally.
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