ArticleJournal of molecular evolution2015
Advances in computer simulation of genome evolution: toward more realistic evolutionary genomics analysis by approximate bayesian computation.
Article in Journal of molecular evolution, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications.Molecular biology and evolution · 2024Review
- Selection among site-dependent structurally constrained substitution models of protein evolution by approximate Bayesian computation.Bioinformatics (Oxford, England) · 2024Article
- Next-generation development and application of codon model in evolution.Frontiers in genetics · 2023Review
- ProteinEvolverABC: coestimation of recombination and substitution rates in protein sequences by approximate Bayesian computation.Bioinformatics (Oxford, England) · 2021Article
- Demographic Histories and Genome-Wide Patterns of Divergence in Incipient Species of Shorebirds.Frontiers in genetics · 2019Article
- Microbial sequence typing in the genomic era.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2018Review
- Article
- Forward-in-Time, Spatially Explicit Modeling Software to Simulate Genetic Lineages Under Selection.Evolutionary bioinformatics online · 2015Article
- Trends in substitution models of molecular evolution.Frontiers in genetics · 2015Article
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Authors and funding
1 author.
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Abstract
NGS technologies present a fast and cheap generation of genomic data. Nevertheless, ancestral genome inference is not so straightforward due to complex evolutionary processes acting on this material such as inversions, translocations, and other genome rearrangements that, in addition to their implicit complexity, can co-occur and confound ancestral inferences. Recently, models of genome evolution that accommodate such complex genomic events are emerging. This letter explores these novel evolutionary models and proposes their incorporation into robust statistical approaches based on computer simulations, such as approximate Bayesian computation, that may produce a more realistic evolutionary analysis of genomic data. Advantages and pitfalls in using these analytical methods are discussed. Potential applications of these ancestral genomic inferences are also pointed out.
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