AIS-Based Bootstrapping of Bayesian Networks for Identifying Protein Energy Route

Authors:
Sungwon Jung;Kyu-Il Cho;Doheon Lee
Affiliations:
Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology, , Daejeon, Republic of Korea 305-701;Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology, , Daejeon, Republic of Korea 305-701;Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology, , Daejeon, Republic of Korea 305-701
Venue:
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Year:
2008

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Abstract

It is important to identify the mechanism of energy transfer in protein structures in understanding their functions. Highly enriched energy in some hot spots of protein structures is transferred to other residues during some functional activity such as binding. The transferred energy reaches at various residues and make them to change their three dimensional structures to make other functional effects. In this paper, we use Bayesian network learning in identifying the route of energy transfer from the estimated energy status of residues. Artificial immune systems (AIS) approach is used for bootstrapping the Bayesian network learning. The analyzed results give a quantitative map of route for energy transfer in 1be9 protein.