Approximation and inference methods for stochastic biochemical kinetics—a tutorial review
D Schnoerr, G Sanguinetti… - Journal of Physics A …, 2017 - iopscience.iop.org
Stochastic fluctuations of molecule numbers are ubiquitous in biological systems. Important
examples include gene expression and enzymatic processes in living cells. Such systems …
examples include gene expression and enzymatic processes in living cells. Such systems …
NNV: the neural network verification tool for deep neural networks and learning-enabled cyber-physical systems
This paper presents the Neural Network Verification (NNV) software tool, a set-based
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
verification framework for deep neural networks (DNNs) and learning-enabled cyber …
Phenotypic switching in gene regulatory networks
Noise in gene expression can lead to reversible phenotypic switching. Several experimental
studies have shown that the abundance distributions of proteins in a population of isogenic …
studies have shown that the abundance distributions of proteins in a population of isogenic …
Conditional moment closure schemes for studying stochastic dynamics of genetic circuits
M Soltani, CA Vargas-Garcia… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Inside individual cells, stochastic expression drives random fluctuations in gene product
copy numbers, which corrupts functioning of both natural and synthetic genetic circuits …
copy numbers, which corrupts functioning of both natural and synthetic genetic circuits …
Stochastic models of gene transcription with upstream drives: exact solution and sample path characterization
J Dattani, M Barahona - Journal of The Royal Society …, 2017 - royalsocietypublishing.org
Gene transcription is a highly stochastic and dynamic process. As a result, the mRNA copy
number of a given gene is heterogeneous both between cells and across time. We present a …
number of a given gene is heterogeneous both between cells and across time. We present a …
Inference for stochastic chemical kinetics using moment equations and system size expansion
Quantitative mechanistic models are valuable tools for disentangling biochemical pathways
and for achieving a comprehensive understanding of biological systems. However, to be …
and for achieving a comprehensive understanding of biological systems. However, to be …
Exact lower and upper bounds on stationary moments in stochastic biochemical systems
In the stochastic description of biochemical reaction systems, the time evolution of statistical
moments for species population counts is described by a linear dynamical system. However …
moments for species population counts is described by a linear dynamical system. However …
Multivariate moment closure techniques for stochastic kinetic models
Stochastic effects dominate many chemical and biochemical processes. Their analysis,
however, can be computationally prohibitively expensive and a range of approximation …
however, can be computationally prohibitively expensive and a range of approximation …
Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry
Most of the fascinating phenomena studied in cell biology emerge from interactions among
highly organized multimolecular structures embedded into complex and frequently dynamic …
highly organized multimolecular structures embedded into complex and frequently dynamic …
Stochastic modeling and numerical simulation of gene regulatory networks with protein bursting
Gene expression is inherently stochastic. Advanced single-cell microscopy techniques
together with mathematical models for single gene expression led to important insights in …
together with mathematical models for single gene expression led to important insights in …