Table of Contents Author Guidelines Submit a Manuscript
BioMed Research International
Volume 2015 (2015), Article ID 394260, 13 pages
Research Article

The Construction of Common and Specific Significance Subnetworks of Alzheimer’s Disease from Multiple Brain Regions

1Information Engineering College, Shanghai Maritime University, Shanghai 201306, China
2DNJ Pharma and Rowan University, Glassboro, NJ 08028, USA
3Psychology Department, The Second People’s Hospital of Guizhou Province, Guiyang 550004, China
4Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received 28 August 2014; Accepted 7 October 2014

Academic Editor: Tao Huang

Copyright © 2015 Wei Kong et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Alzheimer’s disease (AD) is a progressively and fatally neurodegenerative disorder and leads to irreversibly cognitive and memorial damage in different brain regions. The identification and analysis of the dysregulated pathways and subnetworks among affected brain regions will provide deep insights for the pathogenetic mechanism of AD. In this paper, commonly and specifically significant subnetworks were identified from six AD brain regions. Protein-protein interaction (PPI) data were integrated to add molecular biological information to construct the functional modules of six AD brain regions by Heinz algorithm. Then, the simulated annealing algorithm based on edge weight is applied to predicting and optimizing the maximal scoring networks for common and specific genes, respectively, which can remove the weak interactions and add the prediction of strong interactions to increase the accuracy of the networks. The identified common subnetworks showed that inflammation of the brain nerves is one of the critical factors of AD and calcium imbalance may be a link among several causative factors in AD pathogenesis. In addition, the extracted specific subnetworks for each brain region revealed many biologically functional mechanisms to understand AD pathogenesis.