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Computational and Mathematical Methods in Medicine
Volume 2016, Article ID 1782732, 8 pages
Research Article

Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides

1Faculty of Computer Science and Materials Science, University of Silesia, Ulica Zytnia 12, 41-200 Sosnowiec, Poland
2Department of Computer Engineering, Faculty of Electronics, Wroclaw University of Science and Technology, Wybrzeże Wyspianskiego 27, 50-370 Wroclaw, Poland

Received 22 October 2015; Accepted 17 February 2016

Academic Editor: Humberto González-Díaz

Copyright © 2016 Wojciech Wieczorek and Olgierd Unold. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The present paper is a novel contribution to the field of bioinformatics by using grammatical inference in the analysis of data. We developed an algorithm for generating star-free regular expressions which turned out to be good recommendation tools, as they are characterized by a relatively high correlation coefficient between the observed and predicted binary classifications. The experiments have been performed for three datasets of amyloidogenic hexapeptides, and our results are compared with those obtained using the graph approaches, the current state-of-the-art methods in heuristic automata induction, and the support vector machine. The results showed the superior performance of the new grammatical inference algorithm on fixed-length amyloid datasets.