A proximity approach to DNA based clustering analysis

Rohani Binti Abu Bakar, Junzo Watada, Witold Pedrycz

    Research output: Contribution to journalArticle

    19 Citations (Scopus)

    Abstract

    Clustering deals with huge amounts of data and aims at the discovery of their structure which becomes expressed in terms of a collection of clusters - information granules capturing the underlying topology of the data. The objective of this paper is to propose an algorithm to support clustering realized in the form of bio-soft or DNA computing. This approach is of particular interest when dealing with large and heterogeneous data sets and when being faced with an unknown number of clusters. We present the details of the algorithm of proximity clustering and show how the overall computing is supported by the individual mechanisms of DNA processing. We offer a numerical example to illustrate essential aspects of the DNA-based clustering. ICIC International

    Original languageEnglish
    Pages (from-to)1203-1212
    Number of pages10
    JournalInternational Journal of Innovative Computing, Information and Control
    Volume4
    Issue number5
    Publication statusPublished - 2008 May

    Fingerprint

    Clustering Analysis
    Proximity
    DNA
    Clustering
    Information granules
    DNA Computing
    Soft Computing
    Number of Clusters
    Topology
    Processing
    Unknown
    Numerical Examples
    Computing

    Keywords

    • Cluster validity
    • Clustering
    • DNA computing
    • Optimization
    • Proximity

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Information Systems
    • Software
    • Theoretical Computer Science

    Cite this

    A proximity approach to DNA based clustering analysis. / Bakar, Rohani Binti Abu; Watada, Junzo; Pedrycz, Witold.

    In: International Journal of Innovative Computing, Information and Control, Vol. 4, No. 5, 05.2008, p. 1203-1212.

    Research output: Contribution to journalArticle

    Bakar, Rohani Binti Abu ; Watada, Junzo ; Pedrycz, Witold. / A proximity approach to DNA based clustering analysis. In: International Journal of Innovative Computing, Information and Control. 2008 ; Vol. 4, No. 5. pp. 1203-1212.
    @article{cc5735d5cb134ee2ab49068124fd0ddb,
    title = "A proximity approach to DNA based clustering analysis",
    abstract = "Clustering deals with huge amounts of data and aims at the discovery of their structure which becomes expressed in terms of a collection of clusters - information granules capturing the underlying topology of the data. The objective of this paper is to propose an algorithm to support clustering realized in the form of bio-soft or DNA computing. This approach is of particular interest when dealing with large and heterogeneous data sets and when being faced with an unknown number of clusters. We present the details of the algorithm of proximity clustering and show how the overall computing is supported by the individual mechanisms of DNA processing. We offer a numerical example to illustrate essential aspects of the DNA-based clustering. ICIC International",
    keywords = "Cluster validity, Clustering, DNA computing, Optimization, Proximity",
    author = "Bakar, {Rohani Binti Abu} and Junzo Watada and Witold Pedrycz",
    year = "2008",
    month = "5",
    language = "English",
    volume = "4",
    pages = "1203--1212",
    journal = "International Journal of Innovative Computing, Information and Control",
    issn = "1349-4198",
    publisher = "IJICIC Editorial Office",
    number = "5",

    }

    TY - JOUR

    T1 - A proximity approach to DNA based clustering analysis

    AU - Bakar, Rohani Binti Abu

    AU - Watada, Junzo

    AU - Pedrycz, Witold

    PY - 2008/5

    Y1 - 2008/5

    N2 - Clustering deals with huge amounts of data and aims at the discovery of their structure which becomes expressed in terms of a collection of clusters - information granules capturing the underlying topology of the data. The objective of this paper is to propose an algorithm to support clustering realized in the form of bio-soft or DNA computing. This approach is of particular interest when dealing with large and heterogeneous data sets and when being faced with an unknown number of clusters. We present the details of the algorithm of proximity clustering and show how the overall computing is supported by the individual mechanisms of DNA processing. We offer a numerical example to illustrate essential aspects of the DNA-based clustering. ICIC International

    AB - Clustering deals with huge amounts of data and aims at the discovery of their structure which becomes expressed in terms of a collection of clusters - information granules capturing the underlying topology of the data. The objective of this paper is to propose an algorithm to support clustering realized in the form of bio-soft or DNA computing. This approach is of particular interest when dealing with large and heterogeneous data sets and when being faced with an unknown number of clusters. We present the details of the algorithm of proximity clustering and show how the overall computing is supported by the individual mechanisms of DNA processing. We offer a numerical example to illustrate essential aspects of the DNA-based clustering. ICIC International

    KW - Cluster validity

    KW - Clustering

    KW - DNA computing

    KW - Optimization

    KW - Proximity

    UR - http://www.scopus.com/inward/record.url?scp=48249091985&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=48249091985&partnerID=8YFLogxK

    M3 - Article

    AN - SCOPUS:48249091985

    VL - 4

    SP - 1203

    EP - 1212

    JO - International Journal of Innovative Computing, Information and Control

    JF - International Journal of Innovative Computing, Information and Control

    SN - 1349-4198

    IS - 5

    ER -