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Visual Data Mining: Effective Exploration of the Biological Universe

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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8401))

Abstract

Visual Data Mining (VDM) is supported by interactive and scalable network visualization and analysis, which in turn enables effective exploration and communication of ideas within multiple biological and biomedical fields. Large networks, such as the protein interactome or transcriptional regulatory networks, contain hundreds of thousands of objects and millions of relationships. These networks are continuously evolving as new knowledge becomes available, and their content is richly annotated and can be presented in many different ways. Attempting to discover knowledge and new theories within this complex data sets can involve many workflows, such as accurately representing many formats of source data, merging heterogeneous and distributed data sources, complex database searching, integrating results from multiple computational and mathematical analyses, and effectively visualizing properties and results. Our experience with biology researchers has required us to address their needs and requirements in the design and development of a scalable and interactive network visualization and analysis platform, NAViGaTOR, now in its third major release.

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Authors and Affiliations

  1. Princess Margaret Cancer Centre, IBM Life Sciences Discovery Centre, and TECHNA for the Advancement of Technology for Health, University Health Network, TMDT Room 11-314, 101 College Street, Toronto, ON, M5G 1L7, Canada

    David Otasek, Chiara Pastrello & Igor Jurisica

  2. Institute for Medical Informatics, Statistics and Documentation, Research Unit HCI, IBM Watson Think Group, Medical University Graz, Auenbruggerplatz 2/V, A-8036, Graz, Austria

    Andreas Holzinger

  3. Departments of Medical Biophysics and Computer Science, University of Toronto, Canada

    Igor Jurisica

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  1. David Otasek
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  2. Chiara Pastrello
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Editors and Affiliations

  1. Research Unit Human-Computer Interaction, Austrian IBM Watson Think Gruop, Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2/V, 8036, Graz, Austria

    Andreas Holzinger

  2. IBM Life Sciences Discovery Centre, TECHNA for the Advancement of Technology for Health, Princess Margaret Cancer Centre, University Health Network, TMDT Room 11-314, 101 College Street, M5G 1L7, Toronto, ON, Canada

    Igor Jurisica

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Otasek, D., Pastrello, C., Holzinger, A., Jurisica, I. (2014). Visual Data Mining: Effective Exploration of the Biological Universe. In: Holzinger, A., Jurisica, I. (eds) Interactive Knowledge Discovery and Data Mining in Biomedical Informatics. Lecture Notes in Computer Science, vol 8401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43968-5_2

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