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    Area of Science:

    • Bioinformatics
    • Optical Computing
    • Genomics

    Background:

    • Exploring large genome datasets requires efficient sequence alignment.
    • Current computational methods face limitations in speed and scalability for massive genomic data.

    Purpose of the Study:

    • To present a novel optical processing approach for rapid genome sequence exploration.
    • To develop and validate an all-optical system for DNA sequence alignment.

    Main Methods:

    • Utilized an optical correlator for global genome sequence alignment.
    • Employed an extended moiré matching technique for local DNA analysis.
    • Developed a novel three-dimensional artificial neural network for all-optical local DNA alignment.

    Main Results:

    • The proposed optical system demonstrated high accuracy in DNA alignment.
    • Achieved local alignment of 4 million 150-base pair sequences in seconds.
    • Outperformed traditional electrical methods like Basic Local Alignment Search Tool (BLAST) in speed.

    Conclusions:

    • Optical processing offers a powerful and significantly faster alternative for large-scale genome sequence analysis.
    • The developed 3D artificial neural network and optical correlator system represent a breakthrough in bioinformatics processing speed.