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Exploring and visualizing multidimensional data in translational research platforms.

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    Exploring complex patient data is crucial for research. This review highlights 11 tools for visualizing multidimensional clinical and omics data, aiding disease understanding and patient care.

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    Area of Science:

    • Biomedical Informatics
    • Translational Research
    • Data Visualization

    Background:

    • Scientific research increasingly generates large, complex datasets with numerous omics and clinical variables from thousands of patients.
    • Data visualization is essential in early research phases for trend identification, outlier detection, and quality control, especially without dominant initial hypotheses.
    • Effective visualization aids in understanding disease mechanisms and improving patient care.

    Purpose of the Study:

    • To review existing tools for visualizing multidimensional data in translational research platforms.
    • To identify platforms that facilitate the exploration of integrated clinical and omics data.

    Main Methods:

    • A comprehensive review of the biomedical literature was conducted.
    • Platforms enabling visualization and exploration of clinical and omics data in translational research were identified.

    Main Results:

    • Eleven distinct platforms were identified: cBioPortal, interactive genomics patient stratification explorer, Igloo-Plot, The Georgetown Database of Cancer Plus, tranSMART, an unnamed data-cube-based model, Papilio, Caleydo Domino, Qlucore Omics, Oracle Health Sciences Translational Research Center, and OmicsOffice® powered by TIBCO Spotfire.
    • These platforms support the visualization and exploration of complex, multidimensional health data.

    Conclusions:

    • The importance of data visualization tools in healthcare is growing due to increasing data complexity and sources.
    • This review provides a valuable resource for investigators seeking tools to navigate and interpret multidimensional translational research data.
    • Utilizing these visualization platforms can enhance data analysis, leading to better disease insights and improved patient outcomes.