ArticleCommunications biology2019
Representing dynamic biological networks with multi-scale probabilistic models.
Article in Communications biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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Who cites it
16 citing papers in PubMed.
- Experimentally calibrated multiscale model predicts schedule dependent drug combination effects.NPJ systems biology and applications · 2026Article
- Mechanistic modeling of cell viability assays with in silico lineage tracing.PLoS computational biology · 2025Article
- From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies.Molecular biotechnology · 2025Review
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- Phenotypic consequences of logarithmic signaling in MAPK stress response.bioRxiv : the preprint server for biology · 2023Article
- Modelling speciation: Problems and implications.In silico biology · 2023Article
- Predicting the behavior of cerebral aneurysms, a different approach is necessary.Surgical neurology international · 2023Article
- Multiscale modeling in the framework of biological systems and its potential for spaceflight biology studies.iScience · 2022Review
- Small Extracellular Vesicles Propagate the Inflammatory Response After Trauma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Article
- Relating simulation studies by provenance-Developing a family of Wnt signaling models.PLoS computational biology · 2021Article
- Reconstructing Boolean network ensembles from single-cell data for unraveling dynamics in the aging of human hematopoietic stem cells.Computational and structural biotechnology journal · 2021Article
- Genetic compensation prevents myopathy and heart failure in an in vivo model of Bag3 deficiency.PLoS genetics · 2020Article
- Article
- Noncatalytic Bruton's tyrosine kinase activates PLCγThe Journal of biological chemistry · 2020Article
- The ParaHox gene Cdx4 induces acute erythroid leukemia in mice.Blood advances · 2019Article
- Computational Approaches in Theranostics: Mining and Predicting Cancer Data.Pharmaceutics · 2019Review
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dynamic models analyzing gene regulation and metabolism face challenges when adapted to modeling signal transduction networks. During signal transduction, molecular reactions and mechanisms occur in different spatial and temporal frames and involve feedbacks. This impedes the straight-forward use of methods based on Boolean networks, Bayesian approaches, and differential equations. We propose a new approach, ProbRules, that combines probabilities and logical rules to represent the dynamics of a system across multiple scales. We demonstrate that ProbRules models can represent various network motifs of biological systems. As an example of a comprehensive model of signal transduction, we provide a Wnt network that shows remarkable robustness under a range of phenotypical and pathological conditions. Its simulation allows the clarification of controversially discussed molecular mechanisms of Wnt signaling by predicting wet-lab measurements. ProbRules provides an avenue in current computational modeling by enabling systems biologists to integrate vast amounts of available data on different scales.
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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.