Abstract
The knowledge of the functions of protein structures is essential for development of new drugs, better crops and synthetic biochemical. There are numerous experimental methods for determining the protein functions, but because of their complexity the number of protein molecules with undetermined functions is rapidly growing. Thus, there is an evident need for development of computer methods for determining the functions of the protein structures. In this study, we introduce the fuzzy theory for protein active sites detection. We propose a novel fuzzy decision tree (FDT) based method for predicting protein active sites that later could be used for determining the functions of the protein molecules. First, we extract several characteristics of the amino acids. Then, we induce FDTs that would be used to predict the protein active sites. We provide experimental results of the evaluation of the prediction power of the proposed method. Also, our method is compared with other machine learning techniques that could be used for this purpose.
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Mirceva, G., Naumoski, A., Davcev, D. (2012). A Novel Fuzzy Decision Tree Based Method for Detecting Protein Active Sites. In: Kocarev, L. (eds) ICT Innovations 2011. ICT Innovations 2011. Advances in Intelligent and Soft Computing, vol 150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28664-3_5
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DOI: https://doi.org/10.1007/978-3-642-28664-3_5
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