ArticleInternational journal of molecular sciences2009
Robustness in regulatory interaction networks. A generic approach with applications at different levels: physiologic, metabolic and genetic.
Article in International journal of molecular sciences, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 32 citations in OpenAlex.
- Boolean Networks with Classic and New Updating Modes Applied to Genetic Regulation in Some Familial Diseases.International journal of molecular sciences · 2025Article
- Overcoming barriers to early disease intervention.Nature biotechnology · 2020Article
- Entropy as a Robustness Marker in Genetic Regulatory Networks.Entropy (Basel, Switzerland) · 2020Article
- Emergence of a "Cyclosome" in a Primitive Network Capable of Building "Infinite" Proteins.Life (Basel, Switzerland) · 2019Article
- Biological Networks Entropies: Examples in Neural Memory Networks, Genetic Regulation Networks and Social Epidemic Networks.Entropy (Basel, Switzerland) · 2018Article
- Article
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- RNA relics and origin of life.International journal of molecular sciences · 2009Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability). We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode) of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression). We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime) or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control.
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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.