New experimental technologies, such as next generation sequencing, have the potential to revolutionize biology and medicine. Yet, in order to realize this potential, novel computational approaches are needed, which are capable of processing and integrating the enormous amounts of data generated by high-throughput methods. To address this challenge, we have developed the following algorithmic tools:

  • Pascal: The Pathway scoring algorithm is a program for calculating gene score and pathway score p-values from GWAS-summary statistics.
  • Metabomatching is a method to identify compounds from spectral features that jointly associate with genotypes.
  • ISA: The Iterative Signature Algorithm was designed to reduce the complexity of very large sets of data by decomposing it into so-called "modules".
  • ExpressionView is an R package that provides an interactive environment to explore biclusters identified in gene expression data.
  • Cellophane is an ImageJ plugin for the semi-automated quantification of a protein profile along the cell membrane.
  • Hypophen is an open-source software program enabling the semi-automatic phenotyping of growing seedlings from time-lapse images.

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