Evidence map›Paper›PMID 35511713›Full record

ArticleMolecular biology and evolution2022

AliSim: A Fast and Versatile Phylogenetic Sequence Simulator for the Genomic Era.

Nhan Ly-Trong, Suha Naser-Khdour, Robert Lanfear, Bui Quang Minh

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

53 citing papers in PubMed.

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  9. The heterogeneous selection landscape of genome evolution in prokaryotes.Proceedings of the National Academy of Sciences of the United States of America · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Nhan Ly-TrongSchool of Computing, College of Engineering and Computer Science, Australian National University, Canberra, ACT 2600, Australia.ORCID 0000-0001-5668-5027
Suha Naser-KhdourEcology and Evolution, Research School of Biology, College of Science, Australian National University, Canberra, ACT 2600, Australia.
Robert LanfearEcology and Evolution, Research School of Biology, College of Science, Australian National University, Canberra, ACT 2600, Australia.
Bui Quang MinhSchool of Computing, College of Engineering and Computer Science, Australian National University, Canberra, ACT 2600, Australia.ORCID 0000-0002-5535-6560

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sequence simulators play an important role in phylogenetics. Simulated data has many applications, such as evaluating the performance of different methods, hypothesis testing with parametric bootstraps, and, more recently, generating data for training machine-learning applications. Many sequence simulation programmes exist, but the most feature-rich programmes tend to be rather slow, and the fastest programmes tend to be feature-poor. Here, we introduce AliSim, a new tool that can efficiently simulate biologically realistic alignments under a large range of complex evolutionary models. To achieve high performance across a wide range of simulation conditions, AliSim implements an adaptive approach that combines the commonly used rate matrix and probability matrix approaches. AliSim takes 1.4 h and 1.3 GB RAM to simulate alignments with one million sequences or sites, whereas popular software Seq-Gen, Dawg, and INDELible require 2-5 h and 50-500 GB of RAM. We provide AliSim as an extension of the IQ-TREE software version 2.2, freely available at www.iqtree.org, and a comprehensive user tutorial at http://www.iqtree.org/doc/AliSim.

Indexed as

Evolution, MolecularModels, GeneticGenomicsPhylogenySoftwaremolecular evolutionphylogeneticssequence simulation

Identifiers

PMID35511713
PMCPMC9113491

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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.