I’m an Assistant Professor in the Microbiology Cluster at the University of Amsterdam. I am mostly interested in how micro-organisms evolve, and how their environment, shaped by other organisms, affect their evolutionary paths. Thereby I focus on metabolism and antibiotic resistance evolution. My PhD research at the Systemsbiology Department of the VU was focussed on explaining metabolic strategies from their evolutionary optimality, and developing mathematical tools to tackle complex metabolic networks. Afterwards, I focussed more on species interactions in a Postdoc at the Centre for Ecological and Evolutionary Synthesis in Oslo and at the Origins Centre. Recently, I have been looking into evolution in the infant gut microbiome, and therefore I am getting acquainted with metagenomics analyses.
I’m a Postdoc in Medical Microbiology, Erasmus Medical Center, Rotterdam. My background consists of a PhD in Microbial Physiology and Systems and Synthetic Biology, and a MSc in Bioinformatics in Wageningen University and Research.
For the past three years in Erasmus MC, I have been involved in multiple omics studies including genomics, proteomics, transcriptomics and metagenotyping. My main focus is antimicrobial resistance mechanisms. I study their presence and evolution in prokaryotic genomes, and their expression and translation in the phenotype. I also perform outbreak management and research regarding epidemiological species. Recently, NGS (Illumina and Nanopore platform) was introduced for diagnostic purposes, which I contribute in the supervision and implementation.
I am Assistant Professor and group leader in Computational Immunology at Center for Translational Immunology at University Medical Centre Utrecht. I am interested in understanding how heterogeneity in immune cells affect immune functions in healthy and diseased individuals. My group works on the following questions:
Immune cell subset profiling using multi-omic data: with the acquisition of ever-more big data, bioinformatic analysis is becoming a challenge. We are working on several approaches based on graph theory and machine learning to integrate multi-omic data generated from different immune cells to study how the immune system is dysregulated in autoimmunity.
T cell repertoire dynamics: Every T cell carries a T cell receptor (TCR) that is used to sense the presence of foreign antigens infecting our cells. From only 65 TCR genes, our body uses random mutations and new combinations to produce >10E8 TCR receptors. Thus, nearly every T cell that circulates in our blood could carry a unique TCR molecule that can theoretically recognize a unique antigen. Due to the enormous diversity, every individual can mount a very personalized immune response against the same pathogen. It is crucial to understand the specificity of TCRs and their dynamics for personalized medicine and therapeutics of cancer, autoimmunity and infectious diseases.
I’m an Assistant professor in the Integrative Bioinformatics group at the Vrije Universiteit Amsterdam. Previously, I did my PhD in the Systems Biology group of Bas Teusink and Frank Bruggeman, after which I did a postdoc in the Computational Cancer Biology group of Lodewyk Wessels at the Netherlands Cancer Institute.
My research focuses on computational approaches to understand signal transduction networks and the role they play in cancer, and I’m particularly excited about the possibilities of novel single cell technologies. By using a combination of statistical and mechanistic modeling approaches, we aim to bridge the gap between “top down” bioinformatics and “bottom up” systems biology.
Hi! I’m Li-Ting, a PhD student in the group of Jeroen de Ridder at University Medical Center Utrecht. I am interested in bringing scientific advance to clinical application. Currently I am working on using deep learning to identify epigenetic of tumor derived cell-free DNA as a liquid biopsy measure for cancer treatment selection. I am also interested in Nanopore sequencing and it’s application in diagnostics.