ArticleBMC bioinformatics2011
PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
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- Machine learning can distinguish orphans that have resulted from sequence divergence beyond recognition.Bioinformatics advances · 2026Article
- Detecting Interspecific Positive Selection Using Convolutional Neural Networks.Molecular biology and evolution · 2025Article
- Unraveling the genetic diversity and adaptive traits of laboratory pig breeds within the perspective of whole - genome resequencing.BMC genomics · 2025Article
- Integrated transcriptome and metabolome analysis of liver reveals unsynchronized growth mechanisms in blunt-snout bream (Megalobrama amblycephala).BMC genomics · 2025Article
- Seamless, rapid, and accurate analyses of outbreak genomic data using splitGenome research · 2024Article
- Metabolism-associated molecular classification and prognosis signature of head and neck squamous cell carcinoma.Heliyon · 2024Article
- Exploring the Rumen Microbiota and Serum Metabolite Profile of Hainan Black Goats with Different Body Weights before Weaning.Animals : an open access journal from MDPI · 2024Article
- Transcriptome sequencing and metabolome analysis reveal the metabolic reprogramming of partial hepatectomy and extended hepatectomy.BMC genomics · 2023Article
- Design of a pan-betacoronavirus vaccine candidate through a phylogenetically informed approach.Science advances · 2023Article
- Nucleotide Substitutions during Speciation may Explain Substitution Rate Variation.Systematic biology · 2022Article
- phastSim: Efficient simulation of sequence evolution for pandemic-scale datasets.PLoS computational biology · 2022Article
- phastSim: efficient simulation of sequence evolution for pandemic-scale datasets.bioRxiv : the preprint server for biology · 2021Article
- A phylogenetic approach for weighting genetic sequences.BMC bioinformatics · 2021Article
- The search of sequence variants using a constrained protein evolution simulation approach.Computational and structural biotechnology journal · 2020Article
- SELVa: Simulator of evolution with landscape variation.PloS one · 2020Article
- SimSpliceEvol: alternative splicing-aware simulation of biological sequence evolution.BMC bioinformatics · 2019Article
- A non-parametric analytic framework for within-host viral phylogenies and a test for HIV-1 founder multiplicity.Virus evolution · 2019Article
- PQ, a new program for phylogeny reconstruction.BMC bioinformatics · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.
resultsPhyloSim is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, PhyloSim can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing PhyloSim to be adapted to specific needs.
conclusionsClose integration with R and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that PhyloSim will be useful to future studies involving simulated alignments.
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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.