Simon van Heeringen

Research

Biological processes such as development, differentation and morphogenesis require
tighly regulated control of gene expression programs. Many interconnected layers of
regulation impose order and direction on the stochastic processes within the environment
of a living cell. The promoter architecture, the chromatin environment, transcription
factor binding and regulatory signals embedded into the DNA sequence, for instance, all
influence gene transcription. Deciphering the regulatory networks that play a role in
development and disease necessitates a systems-level understanding of gene regulation.
High-throughput genomic techniques enable us to study these mechanisms at an
unprecedented scale and resolution. In my group we develop and apply computational
approaches for analysis and visualization of high-throughput genomic data with the aim
to understand transcription regulation in development, differentation and disease.
Our research covers the interplay between primary DNA sequence and epigenetic mechanisms
and their control of gene expression in two major themes:

  1. regulatory sequence analysis;
  2. computational epigenetics.

Current projects include:

  • Regulation by Polycomb group proteins: sequence analysis of H3K27me3 domains using machine learning methods.
  • De novo motif identification and regulatory sequence analysis in genome-wide datasets.
  • Automatic gene annotation incorporating high-throughput sequencing data (RNA-seq, ChIP-seq).
  • Integrative analysis and visualization of epigenetic regulatory dynamics.