ArticleBMC bioinformatics2013
In silico experimental evolution: a tool to test evolutionary scenarios.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- The path-label reconciliation (PLR) dissimilarity measure for gene trees.Algorithms for molecular biology : AMB · 2025Article
- Genome Streamlining: Effect of Mutation Rate and Population Size on Genome Size Reduction.Genome biology and evolution · 2024Article
- Forward-in-time simulation of chromosomal rearrangements: The invisible backbone that sustains long-term adaptation.Molecular ecology · 2024Article
- Self-replicating artificial neural networks give rise to universal evolutionary dynamics.PLoS computational biology · 2024Article
- Innovation in viruses: fitness valley crossing, neutral landscapes, or just duplications?Virus evolution · 2024Article
- avidaR: an R library to perform complex queries on an ontology-based database of digital organisms.PeerJ. Computer science · 2023Article
- Evolutionary instability of selfish learning in repeated games.PNAS nexus · 2022Article
- Covalent docking and molecular dynamics simulations reveal the specificity-shifting mutations Ala237Arg and Ala237Lys in TEM beta-lactamase.PLoS computational biology · 2022Article
- Simulating the evolutionary trajectories of metabolic pathways for insect symbionts in the genusMicrobial genomics · 2020Article
- Adapting the engine to the fuel: mutator populations can reduce the mutational load by reorganizing their genome structure.BMC evolutionary biology · 2019Article
- Different Evolutionary Paths to Complexity for Small and Large Populations of Digital Organisms.PLoS computational biology · 2016Article
- Evolution of Genome Size in Asexual Digital Organisms.Scientific reports · 2016Article
- Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor.BMC evolutionary biology · 2015Article
- Modeling behavior dynamics using computational psychometrics within virtual worlds.Frontiers in psychology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Comparative genomics has revealed that some species have exceptional genomes, compared to their closest relatives. For instance, some species have undergone a strong reduction of their genome with a drastic reduction of their genic repertoire. Deciphering the causes of these atypical trajectories can be very difficult because of the many phenomena that are intertwined during their evolution (e.g. changes of population size, environment structure and dynamics, selection strength, mutation rates...). Here we propose a methodology based on synthetic experiments to test the individual effect of these phenomena on a population of simulated organisms. We developed an evolutionary model--aevol--in which evolutionary conditions can be changed one at a time to test their effects on genome size and organization (e.g. coding ratio). To illustrate the proposed approach, we used aevol to test the effects of a strong reduction in the selection strength on a population of (simulated) bacteria. Our results show that this reduction of selection strength leads to a genome reduction of ~35% with a slight loss of coding sequences (~15% of the genes are lost--mainly those for which the contribution to fitness is the lowest). More surprisingly, under a low selection strength, genomes undergo a strong reduction of the noncoding compartment (~55% of the noncoding sequences being lost). These results are consistent with what is observed in reduced Prochlorococcus strains (marine cyanobacteria) when compared to close relatives.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.