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Pythofragam: A Python-Based Optimization Tool For Dna Fragment Assembly
Motivation: A python-based tool and allied algorithm is presented that addresses the optimization of DNA fragment assembly using an overlap layout consensus approach. We overcome the problem of reconstructing the original DNA from the fragments. We have explored several possible solutions using an artificial intelligence method called the Restarting and Recentering Hybrid Genetic Algorithm (RRHGA). The fragments are ordered based on minimizing the number of contigs using the Power-Aware Local Search (PALS) algorithm. Summary: A DNA fragment assembly based on the overlap layout consensus approach using the RRHGA is presented. The RRHGA utilizes PALS as an evolutionary operator to order the fragment while minimizing the number of the contig. The proposed framework consists of two objectives: (a) maximizing the sum of the overlapping surface between the two adjacent fragments using the overlap score as a fitness value, and (b) minimizing the number of contigs using PALS as an evolutionary operator. The fitness value and the number of contigs are used as a comparison metric. The framework is evaluated on twenty-five benchmark datasets. Implementation and Availability: The framework and its associated tool are implemented in python and the source code is available at https://github.com/uzmakhann/A-package-for-optimizing-the-DNA-fragment-assembly.