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Computational and Mathematical Methods in Medicine
Volume 2014 (2014), Article ID 891761, 10 pages
http://dx.doi.org/10.1155/2014/891761
Research Article

Dynamic Regulatory Network Reconstruction for Alzheimer’s Disease Based on Matrix Decomposition Techniques

1Information Engineering College, Shanghai Maritime University, Shanghai 201306, China
2DNJ Pharma and Rowan University, NJ 08028, USA
3Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received 18 January 2014; Revised 19 May 2014; Accepted 26 May 2014; Published 15 June 2014

Academic Editor: Volkhard Helms

Copyright © 2014 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.

Abstract

Alzheimer’s disease (AD) is the most common form of dementia and leads to irreversible neurodegenerative damage of the brain. Finding the dynamic responses of genes, signaling proteins, transcription factor (TF) activities, and regulatory networks of the progressively deteriorative progress of AD would represent a significant advance in discovering the pathogenesis of AD. However, the high throughput technologies of measuring TF activities are not yet available on a genome-wide scale. In this study, based on DNA microarray gene expression data and a priori information of TFs, network component analysis (NCA) algorithm is applied to determining the TF activities and regulatory influences on TGs of incipient, moderate, and severe AD. Based on that, the dynamical gene regulatory networks of the deteriorative courses of AD were reconstructed. To select significant genes which are differentially expressed in different courses of AD, independent component analysis (ICA), which is better than the traditional clustering methods and can successfully group one gene in different meaningful biological processes, was used. The molecular biological analysis showed that the changes of TF activities and interactions of signaling proteins in mitosis, cell cycle, immune response, and inflammation play an important role in the deterioration of AD.