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Dongmin Jung

dblp:228/0389 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1

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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genome annotation
functional annotation
0.412020
ShinyGO: a graphical gene-set enrichment tool for animals and plants · Bioinform. 2020
Bioinformatics and computational biology › functional genomics › functional enrichment analysis
gene set enrichment analysis
0.412020
ShinyGO: a graphical gene-set enrichment tool for animals and plants · Bioinform. 2020

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

STRING · 0.4KEGG · 0.4
YearPublicationVenuePosition
2020 ShinyGO: a graphical gene-set enrichment tool for animals and plants
abstract
MOTIVATION: Gene lists are routinely produced from various omic studies. Enrichment analysis can link these gene lists with underlying molecular pathways and functional categories such as gene ontology (GO) and other databases. RESULTS: To complement existing tools, we developed ShinyGO based on a large annotation database derived from Ensembl and STRING-db for 59 plant, 256 animal, 115 archeal and 1678 bacterial species. ShinyGO's novel features include graphical visualization of enrichment results and gene characteristics, and application program interface access to KEGG and STRING for the retrieval of pathway diagrams and protein-protein interaction networks. ShinyGO is an intuitive, graphical web application that can help researchers gain actionable insights from gene-sets. AVAILABILITY AND IMPLEMENTATION: http://ge-lab.org/go/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Steven X. Ge, Dongmin Jung, Runan Yao
Bioinform.2