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Article overview
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Computational Modelling of Plasticity-Led Evolution | | Eden Tian Hwa Ng
; Akira R. Kinjo
; | | Date: |
1 Aug 2022 | | Abstract: | Plasticity-led evolution is a form of evolution where a change in the
environment induces novel traits via phenotypic plasticity, after which the
novel traits are genetically accommodated over generations under the novel
environment. This mode of evolution is deemed to resolve the problem of
gradualism (i.e., evolution by slow accumulation of mutations which induce
phenotypic variation) in face of a large environmental change implied by the
Modern Evolutionary Synthesis. While experimental works are essential for
validating that plasticity-led evolution indeed happened, we need computational
models to gain insight into its underlying mechanisms and make qualitative
predictions. Such computational models should include the developmental process
and gene-environment interactions in addition to genetics and natural
selection. We point out that gene regulatory network models can incorporate all
the above notions. In this review, we highlight results from computational
modelling of gene regulatory networks that consolidate the criteria of
plasticity-led evolution. Since gene regulatory networks are mathematically
equivalent to artificial recurrent neural networks, we also discuss their
analogies and discrepancies, which may help understand the mechanisms
underlying plasticity-led evolution. | | Source: | arXiv, 2208.00649 | | Services: | Forum | Review | PDF | Favorites | |
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