Methods for quantifying how biological systems use and recycle resources are relevant well beyond synthetic biology. In pharmacology too, understanding cellular resource turnover should help clarify the system-level consequences of drug action, engineered pathways, and therapeutic interventions.
The chapter presents a quantitative framework for comparing resource-flow dynamics and causal patterns across different model parameter regimes. As a case study, the chapter examines the E. coli two-component system for inorganic phosphate uptake and shows how synthetic promoter variants affect ATP-related resource economy.

Genetic data is highly sensitive. Sharing genetic data between collaborative partners requires privacy preserving measures. We propose a framework for generating synthetic genotype data that balances privacy and utility for a given metric. The framework combines an iterative feedback-driven optimization process with utility metrics, and membership-inference-based privacy evaluation.

This paper presents an automated temporal schema optimisation approach for NoSQL wide-column stores (specifically Cassandra). It tackles the key challenge of choosing between referencing vs denormalisation strategies by using a cost model that balances read/write performance based on data characteristics and workload patterns. The result: schemas that reduce workload latency by up to three orders of magnitude for the most expensive cases.

"Explaining the causal structure underlying the dynamic function of living systems is a central goal of biology." In this paper, by bridging methods from computer science and computational biology, we address this concern for a setting, broadly used in many systems biology models. Our results provide a means for comparing objects of study in this domain, a fundamental capability that is essential for a deeper understanding in science.

Genetic data is becoming increasingly widespread. It will be even more so in the next decade with decreasing sequencing costs. This paper explores the promising potential of relational databases in storing and querying VCF data at the dawn of the multiomics age in personalised medicine.

In the first chapter of this book, I describe how mathematical modelling realises a computer-aided design vision in creating living technologies based on microorganisms. The aim here is to make synthetic biology a field of engineering rather than a purely experimental discipline based on trial and error.

A tool for examining causal patterns in biological pathways: what downstream effects does a perturbation trigger?

Automated reasoning is hard, so it is no wonder that LMMs struggle with it. Yet, automated provers are pushing the envelope for industrial applications these days. Can we achieve competitive results with analytic provers? That is what I investigate in this paper.

Our paper, accompanying our previous modeling paper, reports observations about early development in Mediterranean corals Corallium rubrum.

Our paper describes the processes that drive early colony formation in Mediterranean corals Corallium rubrum.

Check out our paper to see how epidemics spread on scale-free networks!

Our recent paper demonstrates a mechanism with which bacteria manage their resource economy. Check it out!

Our paper on analysing noise in synthetic biology applications via stochastic simulaitons is now published.