Dimension Reduction for the Integrative Analysis of Multilevel Omics Data

  • Thallinger, G. (Speaker)
  • Bettina Pucher (Contributor)
  • Oana Alina Zeleznik (Contributor)

    Activity: Talk or presentation › Talk at conference or symposium › Science to science

    Description

    Biological systems are increasingly studied at multiple omics levels simultaneously. Sequential analysis of the individual omics levels does not take the interconnected nature of the data into account. Integrative analysis of the multilevel data using dimension reduction techniques facilitate the identification of a larger number and more relevant features than sequential methods. We apply principal component-,
    correspondence- and multiple co-inertia analysis to transcriptome and proteome data from 57 cancer cell lines and show that MCIA allows identification of a more complete set of relevant features and more accurate classification of the cancer types.
    Period5 May 2018
    Event titleSIAM Conference on Applied Linear Algebra
    Event typeConference
    LocationHong Kong, Hong KongShow on map
    Degree of RecognitionInternational

    Fields of Expertise

    • Human- & Biotechnology
    • Information, Communication & Computing

    Treatment code (Nähere Zuordnung)

    • Basic - Fundamental (Grundlagenforschung)