ArticleeLife2020
Inherent regulatory asymmetry emanating from network architecture in a prevalent autoregulatory motif.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Article
- GTAT-GRN: a graph topology-aware attention method with multi-source feature fusion for gene regulatory network inference.Frontiers in genetics · 2025Article
- Regulatory properties of transcription factors with diverse mechanistic function.PLoS computational biology · 2024Article
- Exploring the mono-/bistability range of positively autoregulated signaling systems in the presence of competing transcription factor binding sites.PLoS computational biology · 2022Article
- Tunable transcription factor library for robust quantification of regulatory properties in Escherichia coli.Molecular systems biology · 2022Article
- Controlling gene expression timing through gene regulatory architecture.PLoS computational biology · 2022Article
- A balancing act in transcription regulation by response regulators: titration of transcription factor activity by decoy DNA binding sites.Nucleic acids research · 2021Article
- Quantifying the regulatory role of individual transcription factors in Escherichia coli.Cell reports · 2021Article
- Inherent regulatory asymmetry emanating from network architecture in a prevalent autoregulatory motif.eLife · 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
4 authors.
Funding
Abstract
Predicting gene expression from DNA sequence remains a major goal in the field of gene regulation. A challenge to this goal is the connectivity of the network, whose role in altering gene expression remains unclear. Here, we study a common autoregulatory network motif, the negative single-input module, to explore the regulatory properties inherited from the motif. Using stochastic simulations and a synthetic biology approach in
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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.