ReviewBiophysical journal2020
Stochastic Modeling of Autoregulatory Genetic Feedback Loops: A Review and Comparative Study.
Review in Biophysical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Mixed positive and negative feedback loops drive diverse single-cell gene expression dynamics.Nature communications · 2026Article
- Scaling laws for function diversity and specialization across socioeconomic and biological complex systems.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Coupling mechanisms coordinating mRNA translation with stages of the mRNA lifecycle.RNA biology · 2025Review
- TRENDY: gene regulatory network inference enhanced by transformer.Bioinformatics (Oxford, England) · 2025Article
- A model-based design strategy to engineer miRNA-regulated detection systems.Frontiers in systems biology · 2025Article
- A robust ultrasensitive transcriptional switch in noisy cellular environments.NPJ systems biology and applications · 2024Article
- Effects of microRNA-mediated negative feedback on gene expression noise.Biophysical journal · 2023Article
- Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike.Biophysical journal · 2023Review
- Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics.Nucleic acids research · 2023Article
- Learning of Iterative Learning Control for Flexible Manufacturing of Batch Processes.ACS omega · 2022Article
- Inferring gene regulatory networks from single-cell RNA-seq temporal snapshot data requires higher-order moments.Patterns (New York, N.Y.) · 2021Article
- A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks.Patterns (New York, N.Y.) · 2021Review
- A Stochastic Model of Gene Expression with Polymerase Recruitment and Pause Release.Biophysical journal · 2020Article
- Computation of Single-Cell Metabolite Distributions Using Mixture Models.Frontiers in cell and developmental biology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Autoregulatory feedback loops are one of the most common network motifs. A wide variety of stochastic models have been constructed to understand how the fluctuations in protein numbers in these loops are influenced by the kinetic parameters of the main biochemical steps. These models differ according to 1) which subcellular processes are explicitly modeled, 2) the modeling methodology employed (discrete, continuous, or hybrid), and 3) whether they can be analytically solved for the steady-state distribution of protein numbers. We discuss the assumptions and properties of the main models in the literature, summarize our current understanding of the relationship between them, and highlight some of the insights gained through modeling.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.