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Comprehensive review of models and methods for inferences in bio-chemical reaction networks
The key processes in biological and chemical systems are described by networks of
chemical reactions. From molecular biology to biotechnology applications, computational …
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 …
Dynamic metabolic engineering integrates synthetic logic circuits into cellular systems,
optimizing metabolic fluxes and augmenting biosynthesis of target metabolites. This study …
optimizing metabolic fluxes and augmenting biosynthesis of target metabolites. This study …
Quasi-robust control of biochemical reaction networks via stochastic morphing
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 …
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
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 …
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
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 …
uncertainty of not knowing accurately reaction rates of underlying biochemical reactions …
Inferring distributions from observed mRNA and protein copy counts in genetic circuits
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 …
dynamics of the underlying biological circuits. For genetic circuits, only a few distributions of …
Variational Bayesian inference of hidden stochastic processes with unknown parameters
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 …
the parameters of these processes are not known. This paper adopts a machine learning …