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.
CITATION STYLE
Otasek, D., Pastrello, C., Holzinger, A., & Jurisica, I. (2014). Visual data mining: Effective exploration of the biological universe. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8401, 19–33. https://doi.org/10.1007/978-3-662-43968-5_2
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