Member overview

Technical University of Applied Sciences Wildau / High Perfomance Computing in Life Sciences

Key figures

  • Focus of our research: solving problems from life sciences using mathematical-statistical-informatical approaches and a broad range of algorithms and methods
  • These include, but are not limited to whole genome, transcriptome and epigenome analyses, differential gene expression analysis, modelling of gene-, protein- and metabolic networks, investigation of genomic structural variants (SVs) and biostatistical computation.
  • integrate different types of data
  • development of algorithms for high performance computing (e.g. machine learning) to allow the combination of large-scale datasets
  • identification and prediction of markers for diseases or variations in phenotypes, which could address questions in personalized medicine

We offer

  • Analysis of biological high throughput -omics data e.g.:
    • Genome, epigenome, transcriptome and proteome sequence analysis
    • Expression analysis
    • Gene (structure) annotation
    • Structural variants analysis
  • Systems biology and network modelling
    • Gene regulatory networks
    • Metabolic networks
    • Signal transduction networks
    • Disease models
  • Construction of Databases
  • Development and optimization of algorithms for high performance computing and GPGPU architectures


Please contact us for further information:

Prof. Dr. Heike Pospisil

Technische Hochschule Wildau

+49 3375 508 949