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Ling-Yun Chen

dblp:254/3559 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0003-3159-6831ORCID · reported

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

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

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis
differential expression analysis
0.412019
Performance of gene expression analyses using de novo assembled transcripts in polyploid species · Bioinform. 2019
Bioinformatics and computational biology
gene expression analysis
0.412019
Performance of gene expression analyses using de novo assembled transcripts in polyploid species · Bioinform. 2019
Bioinformatics and computational biology › sequence analysis › sequence assembly
transcriptome assembly
0.412019
Performance of gene expression analyses using de novo assembled transcripts in polyploid species · Bioinform. 2019

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

co-expression network analysis · 0.4
YearPublicationVenuePosition
2019 Performance of gene expression analyses using de novo assembled transcripts in polyploid species
abstract
MOTIVATION: Quality of gene expression analyses using de novo assembled transcripts in species that experienced recent polyploidization remains unexplored. RESULTS: Differential gene expression (DGE) analyses using putative genes inferred by Trinity, Corset and Grouper performed slightly differently across five plant species that experienced various polyploidy histories. In species that lack recent polyploidy events that occurred in the past several millions of years, DGE analyses using de novo assembled transcriptomes identified 54-82% of the differentially expressed genes recovered by mapping reads to the reference genes. However, in species that experienced more recent polyploidy events, the percentage decreased to 21-65%. Gene co-expression network analyses using de novo assemblies versus mapping to the reference genes recovered the same module that significantly correlated with treatment in one species that lacks recent polyploidization. AVAILABILITY AND IMPLEMENTATION: Commands and scripts used in this study are available at https://bitbucket.org/lychen83/chen_et_al_2018_benchmark_dge/; Analysis files are available at Dryad doi: 10.5061/dryad.4p6n481. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Ling-Yun Chen, Diego F. Morales-Briones, Courtney N. Passow, Ya Yang
Bioinform.1