Critical review of data mining techniques for gene expression analysis

Mazin Aouf, Liwan Liyanage, Stephen Hansen

    Research output: Chapter in Book / Conference PaperConference Paper

    Abstract

    ![CDATA[Classification of gene expression data has been exploded in the recent years. This can aid in the development of efficient methodology in the field of bio-informatics to be used for tumours diagnosis and treatment. Data mining is an effective technique being used in this field. One of the most difficulties facing this technology is the inappropriate classification methods that examine complex structure of gene expression data. In this paper, we give a brief introduction of gene expression data with experiment and we have made a critical review of major techniques being applied in the field of gene expression data with help of data mining. It can be seen that researchers have developed various techniques for gene data classification. In addition, they may differ from one to another whereas results are still showing the need for enhancement in this field. Some of these techniques are addressed in this paper in term of advantages and disadvantages. Accordingly, the deoxyribonucleic acid (DNA) is considered as the maestro of the tumour-derived factors. Analyzing changes on the gene expression may give rise for diagnosis enhancement of affected tissues in their early stages. For that reason, an ongoing research is addressing the problem of subspace clustering methodologies suitable for high dimensional datasets and verify of the new methodologies using appropriate datasets, particularly suitable for the analysis of gene expression data. In this context, researchers have identified various limitations of these methods particularly in the areas of information integration systems, text-mining and bio-informatics. In this context, researchers have identified various limitations of these methods particularly in the areas of information integration systems, text-mining and bio-informatics. This paper aims too at providing an overview of the published literature with a particular focus on the current status of subspaces clustering for knowledge discovery toward tumour diagnosis. This is considered to be an essential step in attempt to overcome the limitations and provide effective statistical model in sense of genetic knowledge discovery.]]
    Original languageEnglish
    Title of host publicationSustainable Development through Effective Man-Machine Co-existence : Proceedings of the 4th International Conference on Information and Automation for Sustainability (ICIAfS'08), held in Colombo, Sri Lanka, 12-14 December, 2008
    PublisherIEEE
    Number of pages5
    ISBN (Print)9781424429004
    Publication statusPublished - 2008
    EventInternational Conference on Information and Automation for Sustainability -
    Duration: 12 Dec 2008 → …

    Conference

    ConferenceInternational Conference on Information and Automation for Sustainability
    Period12/12/08 → …

    Keywords

    • DNA
    • data mining
    • bioinformatics
    • tumors
    • gene expression
    • genetic engineering

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