Projects
Full-length transcriptome profiling of KCNQ2-Encephalopthy during development using iPSC-derived neurons. University of Antwerp
Genome and transcriptome engineering with CRISPR/Cas as a precision medicine for Charcot-Marie-Tooth type 2L. University of Antwerp
Unravelling the genetic basis of cryptorchidism in pigs: experimental (design) optimisation and whole transcriptome analysis KU Leuven
The pig sector in Belgium is economically the most important subsector in agriculture with an annual production value of 1.5 billion euro (FOD Economie, 2015). Approximately 11.9 million pigs are being raised and slaughtered annually. An international estimate (Walters, 2016) reveals that on average 3.2% of the pigs suffers from a congenital defect, which would represent 380,000 individuals in Belgium each year. The economic loss caused by ...
Global transcriptome profiling of marine fish in response to environmental change: salinity and ammonia interactions. University of Antwerp
Transcriptome analysis of persister cells in Burkholderia cepacia complex biofilms Ghent University
The goal of this project is to gain a better insight in the molecular mechanisms responsible for antimicrobial resistance in Burkholderia cepacia complex isolates in planktonic and sessile cells. To this end we will carry out a full transcriptome analysis, using microarrays and qPCR
Transcriptome profile of the human placenta: in search of maternal and fetal genetic factors associated with preterm birth. Ghent University
Preterm birth is defined as childbirth before 37 completed weeks of pregnancy. It is the
leading cause of perinatal morbidity and mortality, leading to high costs in care and long-term disability. It accounts for 5-12 % of all live births worldwide. Multiple factors, both endogenous and exogenous to the mother seem to play a role. Genetic factors appear to be involved, as apparent from disparities between racial groups and on familial ...
Development of a data-mining pipeline for drug target identification from circulating transcriptomes of lung cancer patients Ghent University
I will develop a bioinformatics tool to identify drug candidates for lung cancer patients using RNA sequencing data from different blood fractions (circulating tumor cells, exosomes and cell-free circulating nucleic acids), enabling a more precise patient treatment. It will be tested in lung cancer (case study) but the developed tools will also be useful for other cancer types.