Determining the state of single cells using expression and open chromatin data sets

Integrating single-cell transcriptomics and single-cell open chromatin data is a promising approach for disentangling cell types in a tissue while at the same time identifying key regulators underlying the specificity of each cell type. In order to make the most of such data, computational methods need to be developed that can integrate the two data types while decomposing both into cell types. In addition to identifying cell types it is also of interest to characterise the observed transcriptomic profiles in terms of large gene expression events such as the set of signalling pathways that are "on", the cell cycle state, and so on. The main goal of this project is computational method development addressing these questions.


Recent studies have focussed on the microbial surface colonisation of these floating plastics indicating a high diverse community that differs enormously from the indigenous free-living marine community. These studies have also raised concerns on the fact that polymers, mainly in the form of microplastics, accumulate persistent organic pollutants and harbour harmful microbial species that can easily enter the food chain. Biodegradation of plastics in aquatic systems has been suggested by pits visualised by scanning electron microscopy. Plastic degradation has been reported for land waste plastics and is mainly carried out by fungi and bacteria. Unfortunately, very little is known on this process in marine systems. We will take a truly interdisciplinary approach to studying this using model polymer chemistry to create synthetic probes to determine the fate of the plastics and their interactions with microbial communities.