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- W3139965670 abstract "COVID-19 is a pandemic that broke out throughout the world and has a high mobility to transfer between humans. Developing intelligent bioinformatics tools is a mandatory to aid in the analysis of the disease. One of these tools is local aligner which aims to find the longest common subsequence between two biological sequences. Fragmented local aligner technique (FLAT) was developed based on meta-heuristic algorithms to accelerating the alignment process, especially for sequences with huge length. In this paper, the performance of ions motion optimization (IMO) algorithm for implementing FLAT was measured. The performance was poor, and a chaotic parameter was added in the exploration equations of IMO to enhance its performance for FLAT. A set of real proteins having a product length which ranges from 250,000 to 9,000,000 were used as a dataset to test the performance of IMO and its developed version. Besides, COVID-19 virus was aligned using FLAT according to IMO and chaotic IMO to verify the enhancement of IMO. All results were compared to the results founded by Smith–Waterman approach. The tests prove the superiority of chaotic IMO over IMO for implementing FLAT on all datasets." @default.
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- W3139965670 date "2021-01-01" @default.
- W3139965670 modified "2023-10-14" @default.
- W3139965670 title "Chaotic Ions Motion Optimization (CIMO) for Biological Sequences Local Alignment: COVID-19 as a Case Study" @default.
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- W3139965670 doi "https://doi.org/10.1007/978-981-33-6966-5_1" @default.
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