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Probabilistic Retrieval and Visualization of Biologically Relevant Microarray Experiments


Repositories of genome-wide expression studies such as ArrayExpress [1] have been growing rapidly over the last few years and continue to do so. The more experimental data are deposited into these repositories, the more likely it becomes that some of them can provide a meaningful biological context to aid in the planning and analysis of new studies. Retrieval of experiments based on their textual description and experimental design has several shortcomings. First of all, textual description of an experiment or its results is not as information-rich as the actual data itself. Secondly, information about the experimental design alone is only of limited use in retrieving biologically relevant data because it does not reflect the results, which contain the bulk of the information and may reveal unexpected relationships. We introduce novel retrieval methods that incorporate the actual gene expression measurements into the search process, along with visualization tools for interpreting and exploring the results [2].


J Caldas, N Gehlenborg, A Faisal, A Brazma and S Kaski. “Probabilistic Retrieval and Visualization of Biologically Relevant Microarray Experiments” BMC Bioinformatics 10(Suppl 13):P1 (2009).

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