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Related Experiment Video

Updated: Feb 7, 2026

Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
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copMEM: finding maximal exact matches via sampling both genomes.

Szymon Grabowski, Wojciech Bieniecki

    Bioinformatics (Oxford, England)
    |July 31, 2018
    PubMed
    Summary

    We developed copMEM, a novel algorithm for efficiently identifying anchor points (Maximum Exact Matches or MEMs) in large genome comparisons. This single-threaded tool significantly accelerates the process, outperforming existing methods.

    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Genome-to-genome comparisons are crucial for evolutionary and functional studies.
    • Identifying anchor points, or Maximum Exact Matches (MEMs), is essential for sequence alignment.
    • Existing MEM-finding algorithms struggle with the computational demands of large genomes.

    Purpose of the Study:

    • To introduce a novel, efficient algorithm for discovering Maximum Exact Matches (MEMs) between large genomes.
    • To address the performance limitations of current genome comparison tools.

    Main Methods:

    • Developed copMEM, an algorithm utilizing coprime sparse sampling of input genomes.
    • Implemented a single-threaded version of the copMEM algorithm.

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    Main Results:

    • copMEM efficiently computes all MEMs of minimum length 100 between human and mouse genomes in under 2 minutes.
    • The algorithm requires only 7 GB of RAM, demonstrating high memory efficiency.
    • Achieved superior performance compared to existing parallelized solutions.

    Conclusions:

    • copMEM offers a significant advancement in computational efficiency for large-scale genome comparisons.
    • The algorithm provides a practical and fast solution for identifying essential anchor points in genomic sequences.