ArticlePLoS computational biology2020
Information transmission from NFkB signaling dynamics to gene expression.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Long-term quantification and brief-pulse optogenetic perturbation of nucleocytoplasmic GtaC dynamics during Dictyostelium development.microPublication biology · 2026Article
- Individual yeast cells signal at different levels but each with good precision.Royal Society open science · 2025Article
- Changes in SOD and NF-κB Levels inAntioxidants (Basel, Switzerland) · 2024Article
- Signalling Pathways Involved in Microglial Activation in Alzheimer's Disease and Potential Neuroprotective Role of Phytoconstituents.CNS & neurological disorders drug targets · 2024Review
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- Quantifying stimulus-response specificity to probe the functional state of macrophages.Cell systems · 2023Article
- Phytochemicals and Regulation of NF-kB in Inflammatory Bowel Diseases: An Overview of In Vitro and In Vivo Effects.Metabolites · 2023Review
- Computational analysis of 4-1BB-induced NFκB signaling suggests improvements to CAR cell design.Cell communication and signaling : CCS · 2022Article
- Quantifying information of intracellular signaling: progress with machine learning.Reports on progress in physics. Physical Society (Great Britain) · 2022Review
- Time-series transcriptomics and proteomics reveal alternative modes to decode p53 oscillations.Molecular systems biology · 2022Article
- IQCELL: A platform for predicting the effect of gene perturbations on developmental trajectories using single-cell RNA-seq data.PLoS computational biology · 2022Article
- Quantifying information accumulation encoded in the dynamics of biochemical signaling.Nature communications · 2021Article
- iPSC-Derived Microglia for Modeling Human-Specific DAMP and PAMP Responses in the Context of Alzheimer's Disease.International journal of molecular sciences · 2020Article
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Authors and funding
2 authors.
Funding
Abstract
The dynamic signal encoding paradigm suggests that information flows from the extracellular environment into specific signaling patterns (encoding) that are then read by downstream effectors to control cellular behavior. Previous work empirically quantified the information content of dynamic signaling patterns. However, whether this information can be faithfully transmitted to the gene expression level is unclear. Here we used NFkB signaling as a model to understand the accuracy of information transmission from signaling dynamics into gene expression. Using a detailed mathematical model, we simulated realistic NFkB signaling patterns with different degrees of variability. The NFkB patterns were used as an input to a simple gene expression model. Analysis of information transmission between ligand and NFkB and ligand and gene expression allows us to determine information loss in transmission between receptors to dynamic signaling patterns and between signaling dynamics to gene expression. Information loss could occur due to biochemical noise or due to a lack of specificity. We found that noise-free gene expression has very little information loss suggesting that gene expression can preserve specificity in NFkB patterns. As expected, the addition of noise to the gene expression model results in information loss. Interestingly, this effect can be mitigated by a specific choice of parameters that can substantially reduce information loss due to biochemical noise during gene expression. Overall our results show that the cellular capacity for information transmission from dynamic signaling patterns to gene expression can be high enough to preserve ligand specificity and thereby the accuracy of cellular response to environmental cues.
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