Modeling the evolution of molecular systems from a mechanistic perspective

•Current GPM models for studying systems evolution have important shortcomings.•Neutral scenarios are underrepresented in evolutionary systems biology studies.•Evolution after gen(om)e duplication is not modeled adequately in current models.•Improved models may help address the role of genome duplic...

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Veröffentlicht in:Trends in plant science 2014-05, Vol.19 (5), p.292-303
Hauptverfasser: Gutiérrez, Jayson, Maere, Steven
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Maere, Steven
description •Current GPM models for studying systems evolution have important shortcomings.•Neutral scenarios are underrepresented in evolutionary systems biology studies.•Evolution after gen(om)e duplication is not modeled adequately in current models.•Improved models may help address the role of genome duplication in plant evolution. Systems biology-inspired genotype–phenotype mapping models are increasingly being used to study the evolutionary properties of molecular biological systems, in particular the general emergent properties of evolving systems, such as modularity, robustness, and evolvability. However, the level of abstraction at which many of these models operate might not be sufficient to capture all relevant intricacies of biological evolution in sufficient detail. Here, we argue that in particular gene and genome duplications, both evolutionary mechanisms of potentially major importance for the evolution of molecular systems and of special relevance to plant evolution, are not adequately accounted for in most GPM modeling frameworks, and that more fine-grained mechanistic models may significantly advance understanding of how gen(om)e duplication impacts molecular systems evolution.
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subjects emergent properties
Evolution, Molecular
evolutionary systems biology
Gene Duplication
genome duplication
Genome, Plant - genetics
Genotype
genotype–phenotype mapping
Models, Biological
Phenotype
Plants - genetics
Systems Biology
title Modeling the evolution of molecular systems from a mechanistic perspective
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