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Bio-Algorithms and Med-Systems

Editor-in-Chief: Roterman-Konieczna , Irena


CiteScore 2018: 0.29

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Source Normalized Impact per Paper (SNIP) 2018: 0.324

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1896-530X
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A method of predicting the secondary protein structure based on dictionaries

Irena Roterman-Konieczna
  • Department of Bioinformatics and Telemedicine, Jagiellonian University Medical College, Lazarza 16, Krakow, Poland
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Piotr Fabian / Katarzyna Stąpor
Published Online: 2015-08-15 | DOI: https://doi.org/10.1515/bams-2015-0019

Abstract

The shape of a protein chain may be analyzed at different levels of details. The ultimate shape description contains three-dimensional coordinates of all atoms in the chain. In many cases, a description of the local shape, namely secondary structure, is enough to determine some properties of proteins. Although obtaining the full three-dimensional (3D) information also defines the secondary structure, the problem of finding this precise 3D shape (tertiary structure) given only the amino acid sequence is very complex. However, the secondary structure may be found even without having the full 3D information. Many methods have been developed for this purpose. Most of them are based on similarities of the analyzed protein chain to other proteins that are already analyzed and have a known secondary structure. The presented paper proposes a method based on dictionaries of known structures for predicting the secondary structure from either the primary structure or the so-called structural code. Accuracies of up to 79% have been achieved.

Keywords: protein secondary structure prediction; statistical dictionary; structural code

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About the article

Corresponding author: Piotr Fabian, Institute of Computer Science, Silesian Technical University, Akademicka 16, Gliwice, Poland, E-mail:


Received: 2015-06-14

Accepted: 2015-07-22

Published Online: 2015-08-15

Published in Print: 2015-09-01


Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: None declared.

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


Citation Information: Bio-Algorithms and Med-Systems, Volume 11, Issue 3, Pages 163–170, ISSN (Online) 1896-530X, ISSN (Print) 1895-9091, DOI: https://doi.org/10.1515/bams-2015-0019.

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