TY - GEN
T1 - Identification of intra-cellular feedback loops by intermittent step perturbation method
AU - Dong, Chaoyi
AU - Cho, Kwang Hyun
AU - Yoon, Tae Woong
N1 - Funding Information:
This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (M10503010001-07N030100112) and also supported from the Korea Ministry of Science and Technology through the Nuclear Research Grant (M20708000001-07B0800-00110) and the 21C Frontier Microbial Genomics and Application Center Program (Grant MG05-0204-3-0).
PY - 2008
Y1 - 2008
N2 - Feedback loops play pivotal roles in the regulation and control of many important cellular processes such as gene transcription, signal transduction, and metabolism. Hence, identification of feedback loops embedded in biomolecular regulatory networks is crucial to understanding the regulatory mechanisms underlying various cellular processes. In this paper, we introduce an identification method called the intermittent step perturbation method (ISPM) that can efficiently identify and locate feedback connectivities among reacting biomolecules. In particular, a sort of stochastic function called an intermittent step perturbation is applied to excite a given network. Then, we employ a statistical algorithm to analyze the resulting time-series data, thereby discerning any causal connection with a circular causal property. This circular causal property implies the existence of a feedback loop in the regulatory network. Finally, the proposed ISPM is demonstrated through an insulin signal transduction pathway model.
AB - Feedback loops play pivotal roles in the regulation and control of many important cellular processes such as gene transcription, signal transduction, and metabolism. Hence, identification of feedback loops embedded in biomolecular regulatory networks is crucial to understanding the regulatory mechanisms underlying various cellular processes. In this paper, we introduce an identification method called the intermittent step perturbation method (ISPM) that can efficiently identify and locate feedback connectivities among reacting biomolecules. In particular, a sort of stochastic function called an intermittent step perturbation is applied to excite a given network. Then, we employ a statistical algorithm to analyze the resulting time-series data, thereby discerning any causal connection with a circular causal property. This circular causal property implies the existence of a feedback loop in the regulatory network. Finally, the proposed ISPM is demonstrated through an insulin signal transduction pathway model.
KW - Control in system biology
UR - http://www.scopus.com/inward/record.url?scp=79961019580&partnerID=8YFLogxK
U2 - 10.3182/20080706-5-KR-1001.1224
DO - 10.3182/20080706-5-KR-1001.1224
M3 - Conference contribution
AN - SCOPUS:79961019580
SN - 9783902661005
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
BT - Proceedings of the 17th World Congress, International Federation of Automatic Control, IFAC
T2 - 17th World Congress, International Federation of Automatic Control, IFAC
Y2 - 6 July 2008 through 11 July 2008
ER -