Pattern clustering with statistical methods using a DNA-based algorithm

Ikno Kim, Junzo Watada, Witold Pedrycz, Jui Yu Wu

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    Clustering is commonly exploited in engineering, management, and science fields with the objective of revealing structure in pattern data sets. In this article, through clustering we construct meaningful collections of information granules (clusters). Although the underlying goal is obvious, its realization is fully challenging. Given their nature, clustering is a well-known NP-complete problem. The existing algorithms commonly produce some suboptimal solutions. As a vehicle of pattern clustering, we discuss in this article how to use a DNA-based algorithm. We also discuss the details of encoding being used here with statistical methods combined with the DNA-based algorithm for pattern clustering.

    Original languageEnglish
    Article number6208882
    Pages (from-to)100-110
    Number of pages11
    JournalIEEE Transactions on Nanobioscience
    Volume11
    Issue number2
    DOIs
    Publication statusPublished - 2012

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    Keywords

    • DNA-based algorithm
    • ordering method
    • pattern clustering
    • splicing operation
    • statistical method

    ASJC Scopus subject areas

    • Pharmaceutical Science
    • Medicine (miscellaneous)
    • Bioengineering
    • Computer Science Applications
    • Biotechnology
    • Biomedical Engineering
    • Electrical and Electronic Engineering

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