Abstract
In this paper, we focus on protein contact map prediction. We describe a method where contact maps are predicted using decision tree-based model. The algorithm includes the subsequence information between the couple of analyzed amino acids. In order to evaluate the method generalization capabilities, we carry out an experiment using 173 non-homologous proteins of known structures. Our results indicate that the method can assign protein contacts with an average accuracy of 0.34, superior to the 0.25 obtained by the FNETCSS method. This shows that our algorithm improves the accuracy with respect to the methods compared, especially with the increase of protein length.
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© 2011 Springer-Verlag Berlin Heidelberg
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Toca, C.E.S., Márquez Chamorro, A.E., Asencio Cortés, G., Aguilar-Ruiz, J.S. (2011). A Decision Tree-Based Method for Protein Contact Map Prediction. In: Pizzuti, C., Ritchie, M.D., Giacobini, M. (eds) Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics. EvoBIO 2011. Lecture Notes in Computer Science, vol 6623. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20389-3_16
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DOI: https://doi.org/10.1007/978-3-642-20389-3_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20388-6
Online ISBN: 978-3-642-20389-3
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