DNA approach to solve clustering problem based on a mutual order

Rohani Binti Abu Bakar, Junzo Watada, Witold Pedrycz

    Research output: Contribution to journalArticle

    45 Citations (Scopus)

    Abstract

    Clustering is regarded as a consortium of concepts and algorithms that are aimed at revealing a structure in highly dimensional data and arriving at a collection of meaningful relationships in data and information granules. The objective of this paper is to propose a DNA computing to support the development of clustering techniques. This approach is of particular interest when dealing with huge data sets, unknown number of clusters and encountering a heterogeneous character of available data. We present a detailed algorithm and show how the essential components of the clustering technique are realized through the corresponding mechanisms of DNA computing. Numerical examples offer a detailed insight into the performance of the DNA-based clustering.

    Original languageEnglish
    Pages (from-to)1-12
    Number of pages12
    JournalBioSystems
    Volume91
    Issue number1
    DOIs
    Publication statusPublished - 2008 Jan

    Fingerprint

    Cluster Analysis
    DNA
    Clustering
    DNA Computing
    Information granules
    Essential Component
    granules
    Number of Clusters
    methodology
    Unknown
    Numerical Examples

    Keywords

    • Cluster validity
    • Clustering
    • DNA computing and optimization

    ASJC Scopus subject areas

    • Ecology, Evolution, Behavior and Systematics
    • Biotechnology
    • Drug Discovery

    Cite this

    DNA approach to solve clustering problem based on a mutual order. / Bakar, Rohani Binti Abu; Watada, Junzo; Pedrycz, Witold.

    In: BioSystems, Vol. 91, No. 1, 01.2008, p. 1-12.

    Research output: Contribution to journalArticle

    Bakar, Rohani Binti Abu ; Watada, Junzo ; Pedrycz, Witold. / DNA approach to solve clustering problem based on a mutual order. In: BioSystems. 2008 ; Vol. 91, No. 1. pp. 1-12.
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