DNA approach to solve clustering problem based on a mutual order

Rohani Binti Abu Bakar*, Junzo Watada, Witold Pedrycz

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    55 Citations (Scopus)


    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
    Issue number1
    Publication statusPublished - 2008 Jan


    • Cluster validity
    • Clustering
    • DNA computing and optimization

    ASJC Scopus subject areas

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


    Dive into the research topics of 'DNA approach to solve clustering problem based on a mutual order'. Together they form a unique fingerprint.

    Cite this