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Abstract: The prediction of the coordination number (CN) of an amino acid in a protein structure has recently received renewed attention. In a recent paper, Kinjo et al. proposed a realvalued definition of CN and a criterion to map it onto a finite set of classes, in order to predict it using classification approaches. The literature reports several kinds of input information used for CN prediction. The aim of this paper is to assess the performance of a state-of-the-art learning method, Learning... (Update)
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BibTeX entry: (Update)
J. Bacardit, M. Stout, N. Krasnogor, J. Hirst, and J. Blazewicz. Coordination number prediction using learning classifier systems: Performance and interpretability. In GECCO 2006. http://citeseer.ist.psu.edu/bacardit06coordination.html More
@misc{ bacardit06coordination,
author = "J. Bacardit and M. Stout and N. Krasnogor and J. Hirst and J. Blazewicz",
title = "Coordination number prediction using learning classifier systems: Performance
and interpretability",
text = "J. Bacardit, M. Stout, N. Krasnogor, J. Hirst, and J. Blazewicz. Coordination
number prediction using learning classifier systems: Performance and interpretability.
In GECCO 2006.",
year = "2006",
url = "citeseer.ist.psu.edu/bacardit06coordination.html" }
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