ArticlePLoS computational biology2013
Cooperative adaptive responses in gene regulatory networks with many degrees of freedom.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 28 citations in OpenAlex.
- Phenotype selection due to mutational robustness.PloS one · 2024Article
- A linear reciprocal relationship between robustness and plasticity in homeostatic biological networks.PloS one · 2023Article
- Degree of Freedom of Gene Expression in Saccharomyces cerevisiae.Microbiology spectrum · 2022Article
- Dynamical systems approach to evolution-development congruence: Revisiting Haeckel's recapitulation theory.Journal of experimental zoology. Part B, Molecular and developmental evolution · 2022Review
- Evolution enhances mutational robustness and suppresses the emergence of a new phenotype: A new computational approach for studying evolution.PLoS computational biology · 2022Article
- Emergence of cooperative bistability and robustness of gene regulatory networks.PLoS computational biology · 2020Article
- Scale invariance in natural and artificial collective systems: a review.Journal of the Royal Society, Interface · 2017Review
- A Boolean gene regulatory model of heterosis and speciation.BMC evolutionary biology · 2015Article
- Elements of the cellular metabolic structure.Frontiers in molecular biosciences · 2015Article
- Development of cell differentiation in the transition to multicellularity: a dynamical modeling approach.Frontiers in microbiology · 2015Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components.
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