Research interest

Our research is on biophysical modeling and bioinformtics. We often combine these two, which results in an approach where development of bioinformatic methods is facilitated by physical understanding of the underlying biological processes. Current research is outlined below, where our theoretical work is often done in direct collaboration with our experimental colleagues.

COVID-19 transmission dynamics

We combine modeling and data analysis from computational systems biology, with simulation and parameter inference approaches from high energy physics to understand COVID-19 infection progression dynamics.

CRISPR/Cas modeling

CRISPR/Cas is an advanced bacterial immune system, which has revolutionized biotechnology. How is this normally silent system induced? While it is hard to experimentally observe the system dynamics, this can be more readily done mathematically, where we use a combination of biophysical and dynamical system modeling. CRISPR/Cas is a potentially powerful barrier to horizontal gene transfer, so modeling its regulation also helps to better understand how antibiotic resistance and virulence genes are disseminated.

CRISPR/Cas bioinformatics

Our research focus is non-canonical CRISPR/Cas functions. It is becoming increasingly clear that the system is also involved in regulation of endogenous bacterial genes that are mainly associated with bacterial pathogenicity. As the system is active under poorly characterized conditions, the target genes can hardly be systematically identified through experiments alone. We develop (biophysics based) bioinformatics methods for predicting targets of crRNAs and CRISPR-associated small RNAs. We also computationally work on a related problem or CRISPR/Cas adaptation, specifically what sequence determinants allow distinguishing self (host) from non-self (viral) DNA.

Robustness of bacterial gene circuits to cell growth rate changes

As a model, we use restriction-modification (R-M) systems, which are often spread by horizontal gene transfer. Consequently, expression of the restriction enzyme and the methylase has to be tightly regulated during its establishment in a naive bacterial host, which is often exhibited by specialized transcription regulators. These systems come with a variety of architectures (convergent, divergent, linear), where we show that these differences can be explained in terms of few general principles. Our current focus is on how these general dynamical features remain robust under changing cellular growth conditions, which affect crucial intracellular parameters.