Research areas

  • Q Science (General) - bioinformatics, computational biology, epigenetics, transcriptional regulation, R, Python, bash, translocation, genomics, transcriptomics, genetics, single cell, chromatin, histone, myeloid, monocyte, macrophage
  • R Medicine (General) - atherosclerosis, foam cell, plaque, endarterectomy, leukemia, inflammation

Research interests

My main interest is the transcriptional regulation of myeloid cells in health and disease. Myeloid cell differentiation is a fascinatingly plastic procedure, where unstimulated cells morph into highly specialized phenotypes. Dysregulation of this process gives rise to various diseases and syndromes, such as myeloid leukemia, atherosclerosis, rheumatoid arthritis, and bacterial sepsis.

During my graduate training, I worked on the molecular and epigenetic mechanisms behind certain genomic translocation induced forms of acute myeloid leukemia, such as MLL-AF9 and AML-ETO positive leukemias.

My current line of research excitingly combines fundamental macrophage biology  -i.e., the interesting mechanisms behind switching of macrophage activation states at the molecular level- with clinically highly relevant diseases like atherosclerosis.

Macrophage activation is hallmarked by the sequential opening up of chromatin by signal dependent transcription factors which target gene programs for specific activation states (e.g., inflammatory or fibrotic.) Specialized macrophages are primed for transcription of response genes by epigenetic processes like DNA methylation and histone modification, and subsequent RNA-polymerase II promoter stalling.

I am highly interested in this epigenetic component of transcriptional regulation of macrophages, and myeloid cells in general. In order to investigate these processes, I like to deploy genomics and transcriptomics assays such as ChIP- ATAC, and RNA-seq, on a bulk or single-cell level. I am skilled at the execution of these genomewide assays, and adept at analyzing the big data sets they generate. I highly enjoy the computational biology groundwork -coding-, as well as the piecing together of the biological puzzle this entails.


Wet Lab:

  • Genomewide assays
    • ChIP-seq
    • ATAC-seq
    • (sc)RNA-seq
    • CROP-seq
  • Mol Bio
    • CRISPR KO / OE
    • Cloning
    • Viral transduction
    • Transfection
    • CRISPR screen library generation


Computational Biology

  • Analyses of genomewide assays
    • ChIP-seq
    • ATAC-seq
    • RNA-seq
    • Single sell ATAC- and RNA-seq
    • CROP-seq
  • Tools
    • R
      • e.g. DEseq2, Seurat, MUSIC
      • Homebrew package development
    • Python
      • e.g. gimme motifs, fluff, velocyto
    • Bash
      • e.g. HISAT2, MACS2, HOMER
      • Homebrew pipeline development for mapping, peak calling, etc.
    • SLURM
      • Homebrew pipeline development for automated processing of samples on a super cluster.
    • GIT
      • All code deposited and version controlled for reproducibility
      • Renv and conda package management

Research output

  1. Microanatomy of the Human Atherosclerotic Plaque by Single-Cell Transcriptomics

    Research output: Contribution to journalArticleAcademicpeer-review

  2. Transcriptional and epigenetic regulation of macrophages in atherosclerosis

    Research output: Contribution to journalReview articleAcademicpeer-review

View all (30) »

ID: 15698101