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Single-cell NF-κB dynamics reveal digital activation and analogue information processing
TLDR
A stochastic mathematical model is developed that reproduces both the digital and analogue dynamics as well as most gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α-induced NF-κB signalling in various types of cells.
Regulation of gene expression in flux balance models of metabolism.
TLDR
Genome-scale metabolic networks can now be reconstructed based on annotated genomic data augmented with biochemical and physiological information about the organism, and transcriptional regulatory events are incorporated within FBA to further constrain the space of possible network functions.
A Whole-Cell Computational Model Predicts Phenotype from Genotype
TLDR
A whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions is reported, concluding that comprehensive whole- cell models can be used to facilitate biological discovery.
Integrating high-throughput and computational data elucidates bacterial networks
TLDR
This model is able not only to predict the outcomes of high-throughput growth phenotyping and gene expression experiments, but also to indicate knowledge gaps and identify previously unknown components and interactions in the regulatory and metabolic networks.
High-Sensitivity Measurements of Multiple Kinase Activities in Live Single Cells
TLDR
This work describes an easy-to-implement and generalizable technology to generate reporters of kinase activity for individual cells that converts phosphorylation into a nucleocytoplasmic shuttling event that can be measured by epifluorescence microscopy and allows for calculation of active kinase concentrations via a mathematical model.
Metabolic modelling of microbes: the flux-balance approach.
TLDR
Genomic information, coupled with biochemical and strain-specific information, has been used to reconstruct whole-cell metabolic networks for sequenced organisms, but this information is not sufficient to specify completely the metabolic phenotypes that will be expressed under given environmental conditions.
Achieving stability of lipopolysaccharide-induced NF-kappaB activation.
TLDR
Computational modeling of the two TLR4-dependent signaling pathways suggests that one pathway requires a time delay to establish early anti-phase activation of NF-kappaB by the two pathways.
Achieving Stability of Lipopolysaccharide-Induced NF-κB Activation
TLDR
Computational modeling of the two TLR4-dependent signaling pathways suggests that one pathway requires a time delay to establish early anti-phase activation of NF-κB by the two pathways.
Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments
TLDR
Deep convolutional neural networks are an accurate method that require less curation time, are generalizable to a multiplicity of cell types, from bacteria to mammalian cells, and expand live-cell imaging capabilities to include multi-cell type systems.
Metabolic modeling of microbial strains in silico.
TLDR
The use of quantitative analysis methods to generate testable hypotheses and drive experimentation at a whole-genome level signals the advent of a systemic modeling approach to cellular and molecular biology.
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