ArticleTheoretical biology & medical modelling2006
A method for the generation of standardized qualitative dynamical systems of regulatory networks.
Article in Theoretical biology & medical modelling, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
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107 citing papers in PubMed.
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- DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control - An efficient data analysis for cancer research.Computational and structural biotechnology journal · 2024Article
- A Model for the Gene Regulatory Network Along the Arabidopsis Fruit Medio-Lateral Axis: Rewiring the Pod Shatter Process.Plants (Basel, Switzerland) · 2024Article
- Cancer mutationscape: revealing the link between modular restructuring and intervention efficacy among mutations.NPJ systems biology and applications · 2024Article
- Characterization of clinical data for patient stratification in moderate osteoarthritis with support vector machines, regulatory network models, and verification against osteoarthritis Initiative data.Scientific reports · 2024Article
- Pancreatic cancer mutationscape: revealing the link between modular restructuring and intervention efficacy amidst common mutations.bioRxiv : the preprint server for biology · 2024Article
- Biologically meaningful regulatory logic enhances the convergence rate in Boolean networks and bushiness of their state transition graph.Briefings in bioinformatics · 2024Article
- The potential role of ocular and otolaryngological mucus proteins in myalgic encephalomyelitis/chronic fatigue syndrome.Molecular medicine (Cambridge, Mass.) · 2024Article
- Modeling uncertainty: the impact of noise in T cell differentiation.Frontiers in systems biology · 2024Article
- Periodically disturbing biofilms reduces expression of quorum sensing-regulated virulence factors iniScience · 2023Article
- Statistical control of structural networks with limited interventions to minimize cellular phenotypic diversity represented by point attractors.Scientific reports · 2023Article
- Prospects of Novel and Repurposed Immunomodulatory Drugs against Acute Respiratory Distress Syndrome (ARDS) Associated with COVID-19 Disease.Journal of personalized medicine · 2023Review
- Network-based modelling of mechano-inflammatory chondrocyte regulation in early osteoarthritis.Frontiers in bioengineering and biotechnology · 2023Article
- Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization.Frontiers in systems biology · 2023Article
- Synergistic effects of complex drug combinations in colorectal cancer cells predicted by logical modelling.Frontiers in systems biology · 2023Article
47 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundModeling of molecular networks is necessary to understand their dynamical properties. While a wealth of information on molecular connectivity is available, there are still relatively few data regarding the precise stoichiometry and kinetics of the biochemical reactions underlying most molecular networks. This imbalance has limited the development of dynamical models of biological networks to a small number of well-characterized systems. To overcome this problem, we wanted to develop a methodology that would systematically create dynamical models of regulatory networks where the flow of information is known but the biochemical reactions are not. There are already diverse methodologies for modeling regulatory networks, but we aimed to create a method that could be completely standardized, i.e. independent of the network under study, so as to use it systematically.
resultsWe developed a set of equations that can be used to translate the graph of any regulatory network into a continuous dynamical system. Furthermore, it is also possible to locate its stable steady states. The method is based on the construction of two dynamical systems for a given network, one discrete and one continuous. The stable steady states of the discrete system can be found analytically, so they are used to locate the stable steady states of the continuous system numerically. To provide an example of the applicability of the method, we used it to model the regulatory network controlling T helper cell differentiation.
conclusionThe proposed equations have a form that permit any regulatory network to be translated into a continuous dynamical system, and also find its steady stable states. We showed that by applying the method to the T helper regulatory network it is possible to find its known states of activation, which correspond the molecular profiles observed in the precursor and effector cell types.
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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.