Volume 15 Supplement 6

Knowledge Discovery and Interactive Data Mining in Bioinformatics

Research

Edited by Andreas Holzinger, Matthias Dehmer and Igor Jurisica

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. Articles have undergone the journal's standard peer review process for supplements. The Supplement Editors declare that they have no competing interests.

One of the grand challenges in our networked world are the large, complex, and often weakly structured data sets along with the massive amounts of unstructered information. This "big data" challenge (V4 Challenge: Volume, Variety, Velocity, Veracity) is most evident in the biomedical domain: the trend towards personalized medicine (P4 Medicine: Predictive, Preventative, Participatory, Personalized) has resulted in an explosion in the amount of generated biomedical data sets- in particular Omics data (e.g. from genomics, proteomics, metabolomics, lipidomics, transcriptomics, epigenetics, microbiomics, fluxomics, phenomics, etc.). This supplement is a special collection of 7 peer reviewed articles carefully selected to provide an overview of this novel, emerging and important new area.

  1. Research

    Selection of entropy-measure parameters for knowledge discovery in heart rate variability data

    Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multipl...

    Christopher C Mayer, Martin Bachler, Matthias Hörtenhuber, Christof Stocker, Andreas Holzinger and Siegfried Wassertheurer

    BMC Bioinformatics 2014 15(Suppl 6):S2

    Published on: 16 May 2014

  2. Research

    Furby: fuzzy force-directed bicluster visualization

    Cluster analysis is widely used to discover patterns in multi-dimensional data. Clustered heatmaps are the standard technique for visualizing one-way and two-way clustering results. In clustered heatmaps, rows...

    Marc Streit, Samuel Gratzl, Michael Gillhofer, Andreas Mayr, Andreas Mitterecker and Sepp Hochreiter

    BMC Bioinformatics 2014 15(Suppl 6):S4

    Published on: 16 May 2014

  3. Research

    Analysis of biomedical data with multilevel glyphs

    This paper presents multilevel data glyphs optimized for the interactive knowledge discovery and visualization of large biomedical data sets. Data glyphs are three- dimensional objects defined by multiple leve...

    Heimo Müller, Robert Reihs, Kurt Zatloukal and Andreas Holzinger

    BMC Bioinformatics 2014 15(Suppl 6):S5

    Published on: 16 May 2014

  4. Research

    Functional and genetic analysis of the colon cancer network

    Cancer is a complex disease that has proven to be difficult to understand on the single-gene level. For this reason a functional elucidation needs to take interactions among genes on a systems-level into accou...

    Frank Emmert-Streib, Ricardo de Matos Simoes, Galina Glazko, Simon McDade, Benjamin Haibe-Kains, Andreas Holzinger, Matthias Dehmer and Frederick Charles Campbell

    BMC Bioinformatics 2014 15(Suppl 6):S6

    Published on: 16 May 2014

  5. Research

    Knowledge discovery of drug data on the example of adverse reaction prediction

    Antibiotics are the widely prescribed drugs for children and most likely to be related with adverse reactions. Record on adverse reactions and allergies from antibiotics considerably affect the prescription ch...

    Pinar Yildirim, Ljiljana Majnarić, Ozgur Ilyas Ekmekci and Andreas Holzinger

    BMC Bioinformatics 2014 15(Suppl 6):S7

    Published on: 16 May 2014