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Highly scalable algorithms for robust string barcoding.

Bhaskar Dasgupta, Kishori M Konwar, Ion I Mandoiu

    International Journal of Bioinformatics Research and Applications
    |December 1, 2007
    PubMed
    Summary
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    String barcoding offers a new way to identify microorganisms using their genomes. This study develops scalable algorithms for robust string barcoding, achieving near-optimal performance with whole-genome data.

    Area of Science:

    • Genomics
    • Bioinformatics
    • Microbial Identification

    Background:

    • String barcoding is an emerging genomic technique for microbial identification.
    • Scalable and robust algorithms are needed for its practical application.

    Purpose of the Study:

    • To engineer highly scalable algorithms for robust string barcoding.
    • To enable distinguisher selection based on whole genomic sequences.

    Main Methods:

    • Development of scalable algorithms for string barcoding.
    • Distinguisher selection using whole genomic sequences of hundreds of microorganisms.
    • Testing on randomly generated and NCBI genomic data.

    Main Results:

    • Successfully engineered scalable algorithms for robust string barcoding.

    Related Experiment Videos

  • Whole-genome based selection yielded a number of distinguishers close to information-theoretic lower bounds.
  • Methods are feasible on a well-equipped workstation for bacterial-sized genomes.
  • Conclusions:

    • The developed algorithms provide a robust and scalable approach for genomic identification of microorganisms.
    • Whole-genome analysis is efficient for selecting optimal distinguishers in string barcoding.
    • This technique approaches theoretical limits for microbial identification.