ArticleIEEE control systems letters2021
A Predictive Reaction-diffusion Based Model of
Article in IEEE control systems letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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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
3 citing papers in PubMed.
- Understanding the development of bacterial colony: Physiology, new technology, and modeling.Quantitative biology (Beijing, China) · 2025Review
- Combining diffusion and transformer models for enhanced promoter synthesis and strength prediction in deep learning.mSystems · 2025Article
- Practical Understanding of Cancer Model Identifiability in Clinical Applications.Life (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Bacterial colony formations exhibit diverse morphologies and dynamics. A mechanistic understanding of this process has broad implications to ecology and medicine. However, many control factors and their impacts on colony formation remain underexplored. Here we propose a reaction-diffusion based dynamic model to quantitatively describe cell division and colony expansion, where control factors of colony spreading take the form of nonlinear density-dependent function and the intercellular impacts take the form of density-dependent hill function. We validate the model using experimental
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Registered trials
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