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 …
Moment-based inference predicts bimodality in transient gene expression
Recent computational studies indicate that the molecular noise of a cellular process may be
a rich source of information about process dynamics and parameters. However, accessing …
a rich source of information about process dynamics and parameters. However, accessing …
Scalable inference of heterogeneous reaction kinetics from pooled single-cell recordings
Mathematical methods combined with measurements of single-cell dynamics provide a
means to reconstruct intracellular processes that are only partly or indirectly accessible …
means to reconstruct intracellular processes that are only partly or indirectly accessible …
Method of conditional moments (MCM) for the Chemical Master Equation: A unified framework for the method of moments and hybrid stochastic-deterministic models
The time-evolution of continuous-time discrete-state biochemical processes is governed by
the Chemical Master Equation (CME), which describes the probability of the molecular …
the Chemical Master Equation (CME), which describes the probability of the molecular …
Nonlinear mixed-effects modelling for single cell estimation: when, why, and how to use it
Background Studies of cell-to-cell variation have in recent years grown in interest, due to
improved bioanalytical techniques which facilitates determination of small changes with high …
improved bioanalytical techniques which facilitates determination of small changes with high …
Identification of cell‐to‐cell heterogeneity through systems engineering approaches
Cells in a genetically homogeneous cell‐population exhibit a significant degree of
heterogeneity in their responses to an external stimulus. To understand origins and …
heterogeneity in their responses to an external stimulus. To understand origins and …
Designing experiments to understand the variability in biochemical reaction networks
Exploiting the information provided by the molecular noise of a biological process has
proved to be valuable in extracting knowledge about the underlying kinetic parameters and …
proved to be valuable in extracting knowledge about the underlying kinetic parameters and …
A hierarchical, data-driven approach to modeling single-cell populations predicts latent causes of cell-to-cell variability
All biological systems exhibit cell-to-cell variability. Frameworks exist for understanding how
stochastic fluctuations and transient differences in cell state contribute to experimentally …
stochastic fluctuations and transient differences in cell state contribute to experimentally …
Uncoupled analysis of stochastic reaction networks in fluctuating environments
The dynamics of stochastic reaction networks within cells are inevitably modulated by factors
considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy …
considered extrinsic to the network such as, for instance, the fluctuations in ribosome copy …
A nonlinear mixed effects approach for modeling the cell-to-cell variability of Mig1 dynamics in yeast
The last decade has seen a rapid development of experimental techniques that allow data
collection from individual cells. These techniques have enabled the discovery and …
collection from individual cells. These techniques have enabled the discovery and …