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    This study introduces new methods for estimating evolutionary distances between genomes by including intergenic regions in analyses of genome rearrangements like transpositions and reversals. Algorithms were developed and tested for accuracy, improving upon existing models.

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    Area of Science:

    • Computational Biology
    • Evolutionary Genomics
    • Bioinformatics

    Background:

    • Genome rearrangements are crucial evolutionary events impacting large genomic segments.
    • Traditional models often overlook intergenic regions, potentially limiting evolutionary distance accuracy.
    • Intergenic regions are increasingly recognized as important for realistic genomic data analysis.

    Purpose of the Study:

    • To develop and analyze approximation algorithms for genome rearrangement problems that incorporate intergenic regions.
    • To address the computational complexity (NP-hard) of Sorting by Intergenic Transpositions and Sorting by Signed Intergenic Reversals and Intergenic Transpositions.
    • To evaluate the performance of these algorithms on both simulated and real genomic data.

    Main Methods:

    • Formulated the Sorting by Intergenic Transpositions problem and proved its NP-hardness.
    • Developed two approximation algorithms for Sorting by Intergenic Transpositions with approximation factors of 3.5 and 2.5.
    • Formulated the Sorting by Signed Intergenic Reversals and Intergenic Transpositions problem and proved its NP-hardness.
    • Developed two approximation algorithms for Sorting by Signed Intergenic Reversals and Intergenic Transpositions with approximation factors of 3 and 2.5.
    • Implemented and tested all algorithms on real and simulated datasets, including weighted scenarios.

    Main Results:

    • Demonstrated the NP-hardness of both Sorting by Intergenic Transpositions and Sorting by Signed Intergenic Reversals and Intergenic Transpositions.
    • Achieved approximation ratios of 3.5 and 2.5 for intergenic transpositions, and 3 and 2.5 for signed intergenic reversals and transpositions.
    • Validated the practical performance of the developed algorithms through implementation and testing on diverse datasets.

    Conclusions:

    • Incorporating intergenic regions significantly enhances the accuracy of evolutionary distance estimations based on genome rearrangements.
    • The developed approximation algorithms provide efficient solutions for complex genome rearrangement problems, offering improved performance over existing methods.
    • This research lays the groundwork for more sophisticated comparative genomics analyses by accounting for a broader range of genomic features.