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Arthur Zwaenepoel

dblp:243/3412 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0003-1085-2912ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
comparative genomics
1.122024
wgd v2: a suite of tools to uncover and date ancient polyploidy and whole-genome duplication · Bioinform. 2024
wgd - simple command line tools for the analysis of ancient whole-genome duplications · Bioinform. 2019
Bioinformatics and computational biology › phylogenetics › evolutionary history reconstruction
divergence time estimation
0.812024
wgd v2: a suite of tools to uncover and date ancient polyploidy and whole-genome duplication · Bioinform. 2024
Bioinformatics and computational biology
phylogenetics
0.812024
wgd v2: a suite of tools to uncover and date ancient polyploidy and whole-genome duplication · Bioinform. 2024
Bioinformatics and computational biology › comparative genomics
whole-genome duplication analysis
0.412019
wgd - simple command line tools for the analysis of ancient whole-genome duplications · Bioinform. 2019
Bioinformatics and computational biology › molecular evolution › evolutionary bioinformatics › evolutionary genomics
genome evolution
0.112019
wgd - simple command line tools for the analysis of ancient whole-genome duplications · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

phylogenetic dating · 0.8mixture model · 0.8colinearity analysis · 0.4KS distribution construction · 0.4
YearPublicationVenuePosition
2024 wgd v2: a suite of tools to uncover and date ancient polyploidy and whole-genome duplication
abstract
MOTIVATION: Major improvements in sequencing technologies and genome sequence assembly have led to a huge increase in the number of available genome sequences. In turn, these genome sequences form an invaluable source for evolutionary, ecological, and comparative studies. One kind of analysis that has become routine is the search for traces of ancient polyploidy, particularly for plant genomes, where whole-genome duplication (WGD) is rampant. RESULTS: Here, we present a major update of a previously developed tool wgd, namely wgd v2, to look for remnants of ancient polyploidy, or WGD. We implemented novel and improved previously developed tools to (a) construct KS age distributions for the whole-paranome (collection of all duplicated genes in a genome), (b) unravel intragenomic and intergenomic collinearity resulting from WGDs, (c) fit mixture models to age distributions of gene duplicates, (d) correct substitution rate variation for phylogenetic placement of WGDs, and (e) date ancient WGDs via phylogenetic dating of WGD-retained gene duplicates. The applicability and feasibility of wgd v2 for the identification and the relative and absolute dating of ancient WGDs is demonstrated using different plant genomes. AVAILABILITY AND IMPLEMENTATION: wgd v2 is open source and available at https://github.com/heche-psb/wgd.
Hengchi Chen, Arthur Zwaenepoel, Yves Van de Peer
Bioinform.2
2019 wgd - simple command line tools for the analysis of ancient whole-genome duplications
abstract
SUMMARY: Ancient whole-genome duplications (WGDs) have been uncovered in almost all major lineages of life on Earth and the search for traces or remnants of such events has become standard practice in most genome analyses. This is especially true for plants, where ancient WGDs are abundant. Common approaches to find evidence for ancient WGDs include the construction of KS distributions and the analysis of intragenomic colinearity. Despite the increased interest in WGDs and the acknowledgment of their evolutionary importance, user-friendly and comprehensive tools for their analysis are lacking. Here, we present an easy to use command-line tool for KS distribution construction named wgd. The wgd suite provides commonly used KS and colinearity analysis workflows together with tools for modeling and visualization, rendering these analyses accessible to genomics researchers in a convenient manner. AVAILABILITY AND IMPLEMENTATION: wgd is free and open source software implemented in Python and is available at https://github.com/arzwa/wgd. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Arthur Zwaenepoel, Yves Van de Peer
Bioinform.1