A conceptual approach to gene expression analysis enhanced by visual analytics

MELO, Cassio, ORPHANIDES, Constantinos, MCLEOD, Kenneth, AUFAIRE, Marie-Aude, ANDREWS, Simon and BURGER, Albert (2013). A conceptual approach to gene expression analysis enhanced by visual analytics. In: Proceedings of the 28th Annual ACM Symposium on Applied Computing. New York, NY, USA, ACM New York, 1314-1319.

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    Abstract

    The analysis of gene expression data is a complex task for biologists wishing to understand the role of genes in the formation of diseases such as cancer. Biologists need greater support when trying to discover, and comprehend, new relationships within their data. In this paper, we describe an approach to the analysis of gene expression data where overlapping groupings are generated by Formal Concept Analysis and interactively analyzed in a tool called CUBIST. The CUBIST workflow involves querying a semantic database and converting the result into a formal context, which can be simplified to make it manageable, before it is visualized as a concept lattice and associated charts.

    Item Type: Book Section
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Page Range: 1314-1319
    Depositing User: Simon Andrews
    Date Deposited: 16 Jul 2013 13:37
    Last Modified: 12 May 2018 01:54
    URI: http://shura.shu.ac.uk/id/eprint/7158

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