ArticleNPJ systems biology and applications2023
The nonlinearity of regulation in biological networks.
Article in NPJ systems biology and applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analysis of Boolean network models reveals design principles of gene regulatory networks.Science advances · 2024Pooled it
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- Canalization as a stabilizing principle of gene regulatory networks: a discrete dynamical systems perspective.NPJ systems biology and applications · 2026Review
- Bayesian Inference of Gene Regulatory Networks at Stochastic Steady State.bioRxiv : the preprint server for biology · 2026Article
- Rethinking medical education through systems biology to address complexity.NPJ systems biology and applications · 2026Review
- BioLogical: a universal analysis framework for biosystem logical dynamics.Computational and structural biotechnology journal · 2026Article
- scGALA advances graph link prediction-based cell alignment for comprehensive data integration and harmonization.Nature communications · 2025Article
- Microenvironmental signals combine to induce non-additive molecular and phenotypic responses in mammary epithelial cells.iScience · 2025Article
- From Parts to Whole: A Systems Biology Approach to Decoding Milk Fever.Veterinary sciences · 2025Review
- Control of Cellular Differentiation Trajectories for Cancer Reversion.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- iDDN: determining trans-omics network structure and rewiring with integrative differential dependency networks.Bioinformatics advances · 2025Article
- Canalization reduces the nonlinearity of regulation in biological networks.NPJ systems biology and applications · 2024Article
- Developing and comparing deep learning and machine learning algorithms for osteoporosis risk prediction.Frontiers in artificial intelligence · 2024Article
- Is Alzheimer's disease an individual-centered disease? Hypotheses from the atomic levels up to mathematical models for biological systems.Frontiers in neurology · 2024Article
- Modulating the dynamics of NFκB and PI3K enhances the ensemble-level TNFR1 signaling mediated apoptotic response.NPJ systems biology and applications · 2023Article
- Network medicinesJournal of translational medicine · 2023Article
- Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology.Cellular and molecular life sciences : CMLS · 2023Review
- Organoids as complex (bio)systems.Frontiers in cell and developmental biology · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The extent to which the components of a biological system are (non)linearly regulated determines how amenable they are to therapy and control. To better understand this property termed "regulatory nonlinearity", we analyzed a suite of 137 published Boolean network models, containing a variety of complex nonlinear regulatory interactions, using a probabilistic generalization of Boolean logic that George Boole himself had proposed. Leveraging the continuous-nature of this formulation, we used Taylor decomposition to approximate the models with various levels of regulatory nonlinearity. A comparison of the resulting series of approximations of the biological models with appropriate random ensembles revealed that biological regulation tends to be less nonlinear than expected, meaning that higher-order interactions among the regulatory inputs tend to be less pronounced. A further categorical analysis of the biological models revealed that the regulatory nonlinearity of cancer and disease networks could not only be sometimes higher than expected but also be relatively more variable. We show that this variation is caused by differences in the apportioning of information among the various orders of regulatory nonlinearity. Our results suggest that there may have been a weak but discernible selection pressure for biological systems to evolve linear regulation on average, but for certain systems such as cancer, on the other hand, to simultaneously evolve more nonlinear rules.
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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 Socratic graph.