Revista UIS Ingenierías

Vol. 17 No. 2 (2018): Revista UIS Ingenierías
Articles

Protein structure prediction using classification techniques

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  • Christian Charry-Ceballos,
  • Oscar Fernando Bedoya Leiva
Christian Charry-Ceballos
Universidad del Valle
Oscar Fernando Bedoya Leiva
Universidad del Valle
DOI: https://doi.org/10.18273/revuin.v17n2-2018007

Published 2018-06-19

Keywords

  • Bioinformatics,
  • classifiers,
  • structural prediction,
  • proteins,
  • SCOP

How to Cite

Charry-Ceballos, C., & Bedoya Leiva, O. F. (2018). Protein structure prediction using classification techniques. Revista UIS Ingenierías, 17(2), 75–86. https://doi.org/10.18273/revuin.v17n2-2018007
Copyright Notice

Abstract

In this paper, a new protein structure prediction method is presented. Unlike current methods, this work introduces an approach based on supervised classification algorithms during the protein structure prediction. The accuracy of the proposed method was compared to traditional methods such as LFF (Local Feature Frequency) when using the Scop 2,05 dataset. The results indicate that there is a significant difference between these two methods. The proposed method reaches accuracy values of 92.13 %, 96.32 %, 93.05 %, and 76.35 %, at class, fold, superfamily, and family levels, respectively, and the LFF method reaches accuracy values of 85.90 %, 90.54 %, 79.85 % and 67.38 %, for the same structural levels.

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