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

Joint Authors

Wieczorek, Wojciech
Unold, Olgierd

Source

Computational and Mathematical Methods in Medicine

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-03-09

Country of Publication

Egypt

No. of Pages

8

Main Subjects

Medicine

Abstract EN

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.

American Psychological Association (APA)

Wieczorek, Wojciech& Unold, Olgierd. 2016. Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100068

Modern Language Association (MLA)

Wieczorek, Wojciech& Unold, Olgierd. Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1100068

American Medical Association (AMA)

Wieczorek, Wojciech& Unold, Olgierd. Use of a Novel Grammatical Inference Approach in Classification of Amyloidogenic Hexapeptides. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100068

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1100068