Comprehensive review of models and methods for inferences in bio-chemical reaction networks

P Loskot, K Atitey, L Mihaylova - Frontiers in genetics, 2019‏ - frontiersin.org
The key processes in biological and chemical systems are described by networks of
chemical reactions. From molecular biology to biotechnology applications, computational …

Engineering the D-lactic acid responsive promoter/repressor system as dynamic metabolic engineering tool in Lactobacillus delbrueckii subsp. bulgaricus for …

P Mukherjee, S Sivaprakasam - Enzyme and Microbial Technology, 2025‏ - Elsevier
Dynamic metabolic engineering integrates synthetic logic circuits into cellular systems,
optimizing metabolic fluxes and augmenting biosynthesis of target metabolites. This study …

Quasi-robust control of biochemical reaction networks via stochastic morphing

T Plesa, GB Stan, TE Ouldridge… - Journal of the Royal …, 2021‏ - royalsocietypublishing.org
One of the main objectives of synthetic biology is the development of molecular controllers
that can manipulate the dynamics of a given biochemical network that is at most partially …

Modelling and simulation of lac-operon gene expression using heterogeneous parallel platforms

NG Bhat, S Balaji - International Journal of Information Technology, 2023‏ - Springer
Proper functioning of any cell depends on gene regulation. Lac operon plays a major role in
regulating the cell metabolism in bacterial genes. The lac genetic switch exhibits significant …

Elucidating effects of reaction rates on dynamics of the lac circuit in Escherichia coli

K Atitey, P Loskot, P Rees - Biosystems, 2019‏ - Elsevier
Gene expression is regulated by a complex transcriptional network. It is of interest to quantify
uncertainty of not knowing accurately reaction rates of underlying biochemical reactions …

Inferring distributions from observed mRNA and protein copy counts in genetic circuits

K Atitey, P Loskot, P Rees - Biomedical Physics & Engineering …, 2018‏ - iopscience.iop.org
Defining distributions of molecule counts produced in the cell can elucidate stochastic
dynamics of the underlying biological circuits. For genetic circuits, only a few distributions of …

Variational Bayesian inference of hidden stochastic processes with unknown parameters

K Atitey, P Loskot, L Mihaylova - arxiv preprint arxiv:1911.00757, 2019‏ - arxiv.org
Estimating hidden processes from non-linear noisy observations is particularly difficult when
the parameters of these processes are not known. This paper adopts a machine learning …