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Using Reduced Amino-Acid Alphabets and Simulated Annealing to Identify Antimicrobial Peptides

    • Atlantic Technological University

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    The efficient detection of similarity between biological sequences is a fundamental task in bioinformatics. This paper describes a k-mer approach for identifying and classifying antimicrobial peptide sequences using 64-bit encoded multiple spaced seeds and a suite of reduced amino acid alphabets. We implemented and tested the approach using a total of 74 reduced alphabets that were either published, altered using simulated annealing, or randomly generated. Our results show that the approach is very accurate and that all of the reduced alphabets of sizes between 9 and 16 were equally effective and far more accurate than smaller sized alphabets. Our custom designed alphabets exhibited higher sensitivity for some families of AMP than any of the published reduced alphabets that we tested.

    Original languageEnglish
    Title of host publicationPractical Applications of Computational Biology and Bioinformatics, 15th International Conference, PACBB 2021
    EditorsMiguel Rocha, Florentino Fdez-Riverola, Mohd Saberi Mohamad, Roberto Casado-Vara
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages11-21
    Number of pages11
    ISBN (Print)9783030862572
    DOIs
    Publication statusPublished - 2022
    Event15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021 - Salamanca, Spain
    Duration: 6 Oct 20218 Oct 2021

    Publication series

    NameLecture Notes in Networks and Systems
    Volume325 LNNS
    ISSN (Print)2367-3370
    ISSN (Electronic)2367-3389

    Conference

    Conference15th International Conference on Practical Applications of Computational Biology and Bioinformatics, PACBB 2021
    Country/TerritorySpain
    CitySalamanca
    Period6/10/218/10/21

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