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.
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Doncescu, A., Inoue, K., Yamamoto, Y. (2007). Knowledge Based Discovery in Systems Biology Using CF-Induction. In: Okuno, H.G., Ali, M. (eds) New Trends in Applied Artificial Intelligence. IEA/AIE 2007. Lecture Notes in Computer Science(), vol 4570. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73325-6_39
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DOI: https://doi.org/10.1007/978-3-540-73325-6_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73322-5
Online ISBN: 978-3-540-73325-6
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