Gene regulatory networks (GRNs) are one of the most prevalent and fundamental types of biological networks whose main actors are genes regulating other genes. Unfortunately, even the simplest GRNs build up a combinatorial number of possible configurations at the DNA, rendering the emergent dynamical process difficult to analyse and even to write down. We leverage formal methods such as model checking and parameter synthesis, in order to shed light on important biological phenomena such as evolutionary robustness and memory mechanisms in GRNs.
Related works.
Tatjana Petrov, Claudia Igler, Ali Sezgin, Thomas A. Henzinger, Calin C. Guet: Long-lived Transients in Gene Regulatory Networks, Theoretical Computer Science, 2021 [doi, pdf]
Pavol Bokes, Julia Klein, Tatjana Petrov: Accelerating Reactions at the DNA Can Slow Down Transient Gene Expression, Computational Methods in Systems Biology (CMSB 2020) [doi, pdf]
Mirco Giacobbe, Calin C. Guet, Ashutosh Gupta, Thomas A. Henzinger, Tiago Paixao, Tatjana Petrov: Model checking the evolution of gene regulatory networks, In Acta Informatica, 2017 [doi pdf]
Mirco Giacobbe, Calin C. Guet, Ashutosh Gupta, Thomas A. Henzinger, Tiago Paixao, Tatjana Petrov: Model Checking Gene Regulatory Networks, 21st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2015), best paper award [doi pdf slides]