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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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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. |
format | Online Article Text |
id | pubmed-4804041 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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