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

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 cor...

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Detalles Bibliográficos
Autores principales: Wieczorek, Wojciech, Unold, Olgierd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4804041/
https://www.ncbi.nlm.nih.gov/pubmed/27051459
http://dx.doi.org/10.1155/2016/1782732
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author Wieczorek, Wojciech
Unold, Olgierd
author_facet Wieczorek, Wojciech
Unold, Olgierd
author_sort Wieczorek, Wojciech
collection PubMed
description 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.
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spelling pubmed-48040412016-04-05 Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides Wieczorek, Wojciech Unold, Olgierd Comput Math Methods Med Research Article 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. Hindawi Publishing Corporation 2016 2016-03-09 /pmc/articles/PMC4804041/ /pubmed/27051459 http://dx.doi.org/10.1155/2016/1782732 Text en Copyright © 2016 W. Wieczorek and O. Unold. https://creativecommons.org/licenses/by/4.0/ 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.
spellingShingle Research Article
Wieczorek, Wojciech
Unold, Olgierd
Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides
title Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides
title_full Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides
title_fullStr Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides
title_full_unstemmed Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides
title_short Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides
title_sort use of a novel grammatical inference approach in classification of amyloidogenic hexapeptides
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4804041/
https://www.ncbi.nlm.nih.gov/pubmed/27051459
http://dx.doi.org/10.1155/2016/1782732
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