ArticlePloS one2017
Suppressors of selection.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- The effects of herding and dispersal behaviour on the evolution of cooperation on complete networks.Journal of mathematical biology · 2024Article
- Fixation probability in evolutionary dynamics on switching temporal networks.Journal of mathematical biology · 2023Article
- Fixation dynamics on hypergraphs.PLoS computational biology · 2023Article
- Categorizing update mechanisms for graph-structured metapopulations.Journal of the Royal Society, Interface · 2023Article
- Martingales and the fixation time of evolutionary graphs with arbitrary dimensionality.Royal Society open science · 2022Article
- Fixation probabilities in network structured meta-populations.Scientific reports · 2021Article
- Fixation probabilities in evolutionary dynamics under weak selection.Journal of mathematical biology · 2021Article
- Fixation probabilities in graph-structured populations under weak selection.PLoS computational biology · 2021Article
- Transient amplifiers of selection and reducers of fixation for death-Birth updating on graphs.PLoS computational biology · 2020Article
- Computation and Simulation of Evolutionary Game Dynamics in Finite Populations.Scientific reports · 2019Article
- Exploring and mapping the universe of evolutionary graphs identifies structural properties affecting fixation probability and time.Communications biology · 2019Article
- Evolutionary regime transitions in structured populations.PloS one · 2018Article
- Suppressors of selection.PloS one · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inspired by recent works on evolutionary graph theory, an area of growing interest in mathematical and computational biology, we present examples of undirected structures acting as suppressors of selection for any fitness value r > 1. This means that the average fixation probability of an advantageous mutant or invader individual placed at some node is strictly less than that of this individual placed in a well-mixed population. This leads the way to study more robust structures less prone to invasion, contrary to what happens with the amplifiers of selection where the fixation probability is increased on average for advantageous invader individuals. A few families of amplifiers are known, although some effort was required to prove it. Here, we use computer aided techniques to find an exact analytical expression of the fixation probability for some graphs of small order (equal to 6, 8 and 10) proving that selection is effectively reduced for r > 1. Some numerical experiments using Monte Carlo methods are also performed for larger graphs and some variants.
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.