WCSE

Prediction of Secondary Structures of Hemoglobin Using Clonal Selection Algorithm

Abstract— Protein structure prediction is one of the most important research areas in bioinformatics. Knowing the structure of the protein provides significant information about the function of protein. However, it is a challenging process to identify the 3-dimensional structure of a protein. Methods such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy require long duration and high costs, furthermore, these methods are not appropriate for every protein. Artificial intelligence and heuristic methods are preferred in the prediction of 3-dimensional structures of proteins recently because of their significant contribution. In this paper, the use of the Clonal Selection Algorithm (CSA) method for protein secondary structure prediction is studied and the results are compared to other artificial intelligence and heuristic methods. Artificial immune system (AIS) based CSA predicted hemoglobin secondary structure with a high prediction accuracy of 88.38 %.

Index Terms— Artificial immune system, Clonal Selection Algorithm, Hemoglobin, Protein secondary structure prediction.

Burcu ÇARKLI YAVUZ
Department of Information Systems Engineering, Sakarya University, TURKEY
Cengiz SERTKAYA, Nilüfer YURTAY
Department of Computer Engineering, Sakarya University, TURKEY

ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.17Xsrc="http://www.wcse.org/uploadfile/2019/0823/20190823055609629.png" style="width: 120px; height: 68px;" />[Download]

Cite: Burcu ÇARKLI YAVUZ, Cengiz SERTKAYA, Nilüfer YURTAY, "Prediction of Secondary Structures of Hemoglobin Using Clonal Selection Algorithm," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1387-1391, Beijing, 25-27 June, 2017.