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Ion Motion Optimization Algorithm Applied to CpG Island Prediction

Cheng-Hong Yang 1, Ying-Jui Hao 1, and Li-Yeh Chuang 2
1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan
2. Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan

Abstract—In a normal cell, CpG islands are usually unmethylated. When cell is changed by diseases, CpG islands are transformed into hypermethylation. Therefore, correctly predicting the locations of CpG islands provides important information in the biomedical. In this study, the ion motion optimization (IMO) algorithm was implemented to predict CpG islands called CpGIMO. A total of six contigs, chromosome 21 and chromosome 22 were test to compare the efficiency of IMO with other methods for CpG island identification. IMO algorithm resolves local optima entrapment through the force of anion and cation. The results showed that the performance of IMO algorithm is better than the other methods.

Index Terms—methylation, CpG islands, ion motion optimization, chromosome, prediction

Cite: Cheng-Hong Yang, Ying-Jui Hao, and Li-Yeh Chuang, "Ion Motion Optimization Algorithm Applied to CpG Island Prediction," Journal of Life Sciences and Technologies, vol. 4, no. 1, pp. 11-16, June 2016. doi: 10.18178/jolst.4.1.11-16
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