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Zastosuj identyfikator do podlinkowania lub zacytowania tej pozycji: http://hdl.handle.net/20.500.12128/3107
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dc.contributor.authorWieczorek, Wojciech-
dc.contributor.authorUnold, Olgierd-
dc.date.accessioned2018-04-24T06:29:00Z-
dc.date.available2018-04-24T06:29:00Z-
dc.date.issued2016-
dc.identifier.citationComputational and Mathematical Methods in Medicine, 2016, iss. 3/9, art. ID 1782732, s. 1-8pl_PL
dc.identifier.issn1748-670X-
dc.identifier.urihttp://hdl.handle.net/20.500.12128/3107-
dc.description.abstractThe 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.pl_PL
dc.language.isoenpl_PL
dc.rightsUznanie autorstwa 3.0 Polska*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/pl/*
dc.subjectAlgorithmspl_PL
dc.subjectAmyloidpl_PL
dc.subjectCorrelation coefficientpl_PL
dc.subjectBioinformaticspl_PL
dc.subjectHumanspl_PL
dc.subjectPeptidespl_PL
dc.subjectFactual Databasespl_PL
dc.titleUse of a novel grammatical inference approach in classification of amyloidogenic hexapeptidespl_PL
dc.typeinfo:eu-repo/semantics/articlepl_PL
dc.identifier.doi10.1155/2016/1782732-
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