Mathematical models are indispensable for studying the architecture and behavior of intracellular signaling networks. It is common to develop models using phenomenological approximations due to the ...

Stochastic dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in the brain, or the spread of infectious diseases. Petar Jovanovski's Ph.D.

Although dynamical systems models are a powerful tool for analysing microbial ecosystems, challenges in learning these models from complex microbiome datasets and interpreting their outputs limit use.