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Duoyuan Chen

dblp:340/2866 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0001-8621-340XORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › comparative genomics
gene duplication detection
0.612022
Tree2GD: a phylogenomic method to detect large-scale gene duplication events · Bioinform. 2022
Bioinformatics and computational biology › phylogenetics
gene tree reconciliation
0.612022
Tree2GD: a phylogenomic method to detect large-scale gene duplication events · Bioinform. 2022
Bioinformatics and computational biology › phylogenetics
phylogenomics
0.612022
Tree2GD: a phylogenomic method to detect large-scale gene duplication events · Bioinform. 2022
Bioinformatics and computational biology › comparative genomics
whole-genome duplication
0.612022
Tree2GD: a phylogenomic method to detect large-scale gene duplication events · Bioinform. 2022

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

synteny analysis · 0.6sequence alignment · 0.6ks distribution analysis · 0.6
YearPublicationVenuePosition
2022 Tree2GD: a phylogenomic method to detect large-scale gene duplication events
abstract
MOTIVATION: Whole-genome duplication events have long been discovered throughout the evolution of eukaryotes, contributing to genome complexity and biodiversity and leaving traces in the descending organisms. Therefore, an accurate and rapid phylogenomic method is needed to identify the retained duplicated genes on various lineages across the target taxonomy. RESULTS: Here, we present Tree2GD, an integrated method to identify large-scale gene duplication events by automatically perform multiple procedures, including sequence alignment, recognition of homolog, gene tree/species tree reconciliation, Ks distribution of gene duplicates and synteny analyses. Application of Tree2GD on 2 datasets, 12 metazoan genomes and 68 angiosperms, successfully identifies all reported whole-genome duplication events exhibited by these species, showing effectiveness and efficiency of Tree2GD on phylogenomic analyses of large-scale gene duplications. AVAILABILITY AND IMPLEMENTATION: Tree2GD is written in Python and C++ and is available at https://github.com/Dee-chen/Tree2gd. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Duoyuan Chen, Taikui Zhang, Yamao Chen
Bioinform.1