DNA Fragment Assembly Using Hybridized Catfish PSO

DNA fragment assembly aids in uncovering several aspects of the human DNA, and hence in-turn enables scientists in understanding and curing several hereditary problems. Several computational methods have been proposed to solve this problem. However, the huge size and the NP-hard nature of the problem poses several challenges in proposing a time effective system for fragment assembly. This paper proposes a hybridized catfish PSO model for the process of fragment assembly. PSO algorithm is enhanced by incorporating the catfish particles to enable the model to get out of the local optimal solutions. Further, the local search process has been hybridized to incorporate simulated annealing, such that the model performs faster selection of solutions. This has enabled the proposed model to provide effective results with low computational requirements. Experiments were performed with 10 benchmark instances from GenFrag. The results were compared with state-of-the-art models in literature, and it was identified that the proposed model exhibits high performance in comparatively shorter time.

Automated summary

This paper presents a hybrid catfish PSO model for DNA fragment assembly, which incorporates catfish particles and simulated annealing to improve performance and efficiency. Experimental results demonstrate that the proposed model outperforms state-of-the-art models in terms of performance within a shorter time frame.