Knowledge based discovery in systems biology using CF-induction

Authors:
Andrei Doncescu;Katsumi Inoue;Yoshitaka Yamamoto
Affiliations:
National Institute of Informatics, Tokyo, Japan and LAAS-CNRS, Toulouse, France;National Institute of Informatics, Tokyo, Japan and Department of Informatics, Graduate University for Advanced Studies, Tokyo, Japan;Department of Informatics, Graduate University for Advanced Studies, Tokyo, Japan
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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Abstract

The cell is an entity composed of several thousand types of interacting proteins. Our goal is to comprehend the biological system using only the revelent information which means that we will be able to reduce or to indicate the main metabolites necessary to measure. In this paper, it is shown how the Artificial Intelligence description method functioning on the basis of Inductive Logic Programming can be used successfully to describe essential aspects of cellular regulation. The results obtained shows that the ILP tool CF-induction discovers the activities of enzymes on glycolyse metabolic pathway when only partial information about it has been used. This procedure is based on the filtering of the high processes to reduce the space search.