IT Revolutions. First International ICST Conference, IT Revolutions 2008, Venice, Italy, December 17-19, 2008, Revised Selected Papers

Research Article

An Integrative Bioinformatics Approach for Knowledge Discovery

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  • @INPROCEEDINGS{10.1007/978-3-642-03978-2_24,
        author={Lourdes Pe\`{o}a-Castillo and Sieu Phan and Fazel Famili},
        title={An Integrative Bioinformatics Approach for Knowledge Discovery},
        proceedings={IT Revolutions. First International ICST Conference, IT Revolutions 2008, Venice, Italy, December 17-19, 2008, Revised Selected Papers},
        proceedings_a={IT REVOLUTIONS},
        year={2012},
        month={5},
        keywords={Bioinformatics knowledge discovery genetic diseases},
        doi={10.1007/978-3-642-03978-2_24}
    }
    
  • Lourdes Peña-Castillo
    Sieu Phan
    Fazel Famili
    Year: 2012
    An Integrative Bioinformatics Approach for Knowledge Discovery
    IT REVOLUTIONS
    Springer
    DOI: 10.1007/978-3-642-03978-2_24
Lourdes Peña-Castillo1,*, Sieu Phan1,*, Fazel Famili1,*
  • 1: National Research Council Canada
*Contact email: lourdes.pena-castillo@nrc-cnrc.gc.ca, sieu.phan@nrc-cnrc.gc.ca, fazel.famili@nrc-cnrc.gc.ca

Abstract

The vast amount of data being generated by large scale omics projects and the computational approaches developed to deal with this data have the potential to accelerate the advancement of our understanding of the molecular basis of genetic diseases. This better understanding may have profound clinical implications and transform the medical practice; for instance, therapeutic management could be prescribed based on the patient’s genetic profile instead of being based on aggregate data. Current efforts have established the feasibility and utility of integrating and analysing heterogeneous genomic data to identify molecular associations to pathogenesis. However, since these initiatives are data-centric, they either restrict the research community to specific data sets or to a certain application domain, or force researchers to develop their own analysis tools. To fully exploit the potential of omics technologies, robust computational approaches need to be developed and made available to the community. This research addresses such challenge and proposes an integrative approach to facilitate knowledge discovery from diverse datasets and contribute to the advancement of genomic medicine.