A Catfish Binary Particle Swarm Optimization for Operon Prediction

Cheng-Huei Yang, Li-Yeh Chuang, Yi-Cheng Chiang, and Cheng-Hong Yang


Operon prediction, CatfishBPSO, intergenic distance, metabolic pathway, cluster of orthologous groups


An operon is a fundamental unit of transcription usually used to understand the regulation and functions of genes within entire genomes. Experimentally detecting operons is difficult and time-consuming and the development of an accurate prediction method would advance gene investigations. Many algorithms and biological properties are currently used in operon prediction, but method and experimental results can still be improved. This study uses a catfish binary particle swarm optimization (CatfishBPSO) for operon prediction in bacterial genomes. The intergenic distance, metabolic pathway and cluster of orthologous groups (COG) gene functions of the Escherichia coli genome are used to design a fitness function. We tested several data to illustrate the effectiveness of our method. Experimental results show that the detection accuracy of the proposed method reached 0.926, 0.941, 0.95 and 0.963 respectively for the B. subtilis, P. aeruginosa PA01, S. aureus and M. tuberculosis genomes. This method can obtains high degree of accuracy, and although add the catfish effect but does not increase the time complexity of PSO.

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