This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Model-Based Identification And Adaptive Control Of The Core Module In A Typical Cell Cycle Pathway Via Network And System Control Theories

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
BINHUA TANG (Department of Biomedical Engineering, Tongji University, Shanghai, China)
LI HE (Department of Electronics & Communications, Sun Yat-Sen University, Guangzhou, China)
QING JING (Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China)
BAIRONG SHEN () (Center for Systems Biology, Soochow University, Suzhou, China)
Abstract

The loss of cell cycle control is often associated with cancers and other different diseases. With the accumulation of omics data, the network for molecule interactions in the cell cycle process will become much clearer. The identification of the crucial modules in a giant network and investigation of inherent control relations are very important to the understanding of the molecular mechanisms of diseases for new drug design. The paper proposes novel techniques in analyzing such core regulatory modules based on network and system control theories. We initially define the degree of participation (DOP) and the rate of activity (ROA) for indentifying core module components, and then the diverse contribution elasticity functions for quantifying pairwise regulatory or control activities between those components, thus facilitating the decomposition of expanded core modules and the formation of feedback loops within the control schema. Motivated by the inherent regulatory mechanisms, we expound a kind of multiphase nonlinear adaptive control algorithm in repelling abnormal genetic mutations, which directly and indirectly impact cancer development in biological cells and organs. Experimental predictions are also elucidated within the work, helping those in vivo design, verification and performance evaluation.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.worldscinet.com/cgi-bin/details.cgi?type=pdf&id=pii:S0219525909002076
File Format: application/pdf
File Function:
Download Restriction: Access to full text is restricted to subscribers.
File URL: http://www.worldscinet.com/cgi-bin/details.cgi?type=html&id=pii:S0219525909002076
File Format: text/html
File Function:
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Publisher Info
Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal Advances in Complex Systems.

Volume (Year): 12 (2009)
Issue (Month): 01 ()
Pages: 21-43
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:wsi:acsxxx:v:12:y:2009:i:01:p:21-43

Contact details of provider:
Web page: http://www.worldscinet.com/acs/acs.shtml

Order Information:
Email:

For technical questions regarding this item, or to correct its listing, contact: (Tai Tone Lim).

Related research
Keywords: Core module; systems theory; contribution elasticity; feedback loop; adaptive control;

Statistics
Access and download statistics

Did you know? Springer Verlag was the first commercial publisher to be listed on RePEc.

This page was last updated on 2010-1-4.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.