ArticleJournal of the Royal Society, Interface2019
Model genotype-phenotype mappings and the algorithmic structure of evolution.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Integrating evolutionary signals and predicted protein structure reveals localized molecular divergence in Cereus lineages.Genetica · 2026Article
- Accessible and robust machine learning approaches to improve the opsin genotype-phenotype map.Molecular biology and evolution · 2026Article
- Article
- The Use of AI for Phenotype-Genotype Mapping.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Maximum mutational robustness in genotype-phenotype maps follows a self-similar blancmange-like curve.Journal of the Royal Society, Interface · 2023Article
- Interpreting T-cell search "strategies" in the light of evolution under constraints.PLoS computational biology · 2023Article
- The structure of genotype-phenotype maps makes fitness landscapes navigable.Nature ecology & evolution · 2022Article
- Genetic architecture of dispersal and local adaptation drives accelerating range expansions.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer.Dynamic games and applications · 2022Review
- Conditional prediction of consecutive tumor evolution using cancer progression models: What genotype comes next?PLoS computational biology · 2021Article
- The role of memory in non-genetic inheritance and its impact on cancer treatment resistance.PLoS computational biology · 2021Article
- The Pathophysiology of Rett Syndrome With a Focus on Breathing Dysfunctions.Physiology (Bethesda, Md.) · 2020Review
- Observation and Control of Gene Expression Noise: Barrier Crossing Analogies Between Drug Resistance and Metastasis.Frontiers in genetics · 2020Article
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4 authors.
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Abstract
Cancers are complex dynamic systems that undergo evolution and selection. Personalized medicine approaches in the clinic increasingly rely on predictions of tumour response to one or more therapies; these predictions are complicated by the inevitable evolution of the tumour. Despite enormous amounts of data on the mutational status of cancers and numerous therapies developed in recent decades to target these mutations, many of these treatments fail after a time due to the development of resistance in the tumour. The emergence of these resistant phenotypes is not easily predicted from genomic data, since the relationship between genotypes and phenotypes, termed the genotype-phenotype (GP) mapping, is neither injective nor functional. We present a review of models of this mapping within a generalized evolutionary framework that takes into account the relation between genotype, phenotype, environment and fitness. Different modelling approaches are described and compared, and many evolutionary results are shown to be conserved across studies despite using different underlying model systems. In addition, several areas for future work that remain understudied are identified, including plasticity and bet-hedging. The GP-mapping provides a pathway for understanding the potential routes of evolution taken by cancers, which will be necessary knowledge for improving personalized therapies.
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