Adaptive models for gene networks.
TLDR
This study demonstrates that the behavior of the p53-MDM2 gene network in individual cells can be tracked using adaptive filtering algorithms and the resulting time-variant models can approximate experimental measurements more accurately than time-invariant models.Abstract:
Biological systems are often treated as time-invariant by computational models that use fixed parameter values In this study, we demonstrate that the behavior of the p53-MDM2 gene network in individual cells can be tracked using adaptive filtering algorithms and the resulting time-variant models can approximate experimental measurements more accurately than time-invariant models Adaptive models with time-variant parameters can help reduce modeling complexity and can more realistically represent biological systemsread more
Citations
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Journal ArticleDOI
Post-translational regulation enables robust p53 regulation
TL;DR: Feedback control and adaptive estimation theories revealed that post-translational regulation achieves a better trade-off than transcriptional regulation, contributing to a more steady level of p53 under the influence of noise and disturbances.
Journal ArticleDOI
Digital Signal Processing and Control for the Study of Gene Networks.
TL;DR: The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.
Proceedings ArticleDOI
Using an adaptive gene network model for self-organizing multicellular behavior
TL;DR: The proposed adaptive modeling approach can be a useful tool in the study of self-organizing behavior observed in other contexts in biology, including microbial pathogenesis, antibiotic resistance, embryonic development, tumor formation, etc.
Proceedings ArticleDOI
An approach to identification procedures for PID control with PLC implementation
TL;DR: This paper presents implementation of identification procedures and control performance monitoring functions in programmable logic controllers (PLC) for PID control with PLC implementation.
Posted ContentDOI
Experimental control of macrophage pro-inflammatory dynamics using predictive models
TL;DR: A model-predictive control framework to temporally regulate macrophage polarization and overall inflammatory regulation to a broad number of diseases is developed and will have numerous applications for regulating immune activity dynamics in chronic inflammatory diseases.
References
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Book
System Identification: Theory for the User
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Journal ArticleDOI
Surfing the p53 network
TL;DR: The p53 tumour-suppressor gene integrates numerous signals that control cell life and death, and the disruption of p53 has severe consequences when a highly connected node in the Internet breaks down.
Journal ArticleDOI
Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences
TL;DR: Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others, including the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
Journal ArticleDOI
Stochasticity in gene expression: from theories to phenotypes
TL;DR: Stochasticity in gene expression can provide the flexibility needed by cells to adapt to fluctuating environments or respond to sudden stresses, and a mechanism by which population heterogeneity can be established during cellular differentiation and development.
Journal ArticleDOI
The first 30 years of p53: growing ever more complex
Arnold J. Levine,Moshe Oren +1 more
TL;DR: Thirty years ago p53 was discovered as a cellular partner of simian virus 40 large T-antigen, the oncoprotein of this tumour virus, and new functions of this protein were revealed, including the regulation of metabolic pathways and cytokines that are required for embryo implantation.