An integrated genetics approach for identifying protein signal pathways of Alzheimer's disease

Yue Huang, Xuezhi Sun and Guangshu Hu

Computer Methods in Biomechanics and Biomedical Engineering, 2011, vol. 14, issue 04, 371-378

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.

Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2010.482525 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:14:y:2011:i:04:p:371-378

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2010.482525

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().