Fuzzy Pattern Trees for Protein Binding Sites Prediction Using Weighted Averaging Fuzzy Aggregation Operators

Mircheva, Georgina and Kulakov, Andrea (2013) Fuzzy Pattern Trees for Protein Binding Sites Prediction Using Weighted Averaging Fuzzy Aggregation Operators. In: Proceedings of the Tenth Conference on Informatics and Information Technology. Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje, Macedonia, Skopje, Macedonia, pp. 102-105. ISBN 978-608-4699-01-9

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Abstract

The knowledge about the relationship between the protein functions and structure is very essential, since it could be used for drug design. With the high-throughput technologies the number of determined protein structures grows rapidly. However, many of these protein structures are not investigated in terms of determining their functions. Thus, the necessity for fast computational methods for annotating protein structures is evident. The functions of the protein structures could be determined by using different information. In our research we focus on annotating protein structures by detecting the protein binding sites. We have already introduced the fuzzy pattern tree induction for predicting the protein binding sites by considering the features of the amino acid residues. In this paper we introduce two additional fuzzy aggregation operators. We present some results of the evaluation of the method regarding the usage of different fuzzy aggregation operators. The results show that the prediction power of the models is increased with the inclusion of the additional fuzzy aggregation operators.

Item Type: Book Section
Subjects: International Conference on Informatics and Information Technologies > Intelligent Systems
International Conference on Informatics and Information Technologies > Robotics
International Conference on Informatics and Information Technologies > Bioinformatics
Depositing User: Vangel Ajanovski
Date Deposited: 28 Oct 2016 00:15
Last Modified: 28 Oct 2016 00:15
URI: http://eprints.finki.ukim.mk/id/eprint/11102

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