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Li-Gen Wang

dblp:158/8439 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 2

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
ChIP-seq analysis
0.212015
ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization · Bioinform. 2015
Bioinformatics and computational biology › genomics
disease genomics
0.212015
DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis · Bioinform. 2015
Bioinformatics and computational biology
epigenomics
0.212015
ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization · Bioinform. 2015

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

visualization · 0.2semantic similarity computation · 0.2peak annotation · 0.2overlap analysis · 0.2hypergeometric model · 0.2gene set enrichment analysis · 0.2
YearPublicationVenuePosition
2015 ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization
abstract
UNLABELLED: ChIPseeker is an R package for annotating ChIP-seq data analysis. It supports annotating ChIP peaks and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions. Comparison of ChIP peak profiles and annotation are also supported. Moreover, it supports evaluating significant overlap among ChIP-seq datasets. Currently, ChIPseeker contains 15 000 bed file information from GEO database. These datasets can be downloaded and compare with user's own data to explore significant overlap datasets for inferring co-regulation or transcription factor complex for further investigation. AVAILABILITY AND IMPLEMENTATION: ChIPseeker is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/ChIPseeker.html).
Guangchuang Yu, Li-Gen Wang, Qing-Yu He
Bioinform.2
2015 DOSE: an R/Bioconductor package for disease ontology semantic and enrichment analysis
abstract
SUMMARY: Disease ontology (DO) annotates human genes in the context of disease. DO is important annotation in translating molecular findings from high-throughput data to clinical relevance. DOSE is an R package providing semantic similarity computations among DO terms and genes which allows biologists to explore the similarities of diseases and of gene functions in disease perspective. Enrichment analyses including hypergeometric model and gene set enrichment analysis are also implemented to support discovering disease associations of high-throughput biological data. This allows biologists to verify disease relevance in a biological experiment and identify unexpected disease associations. Comparison among gene clusters is also supported. AVAILABILITY AND IMPLEMENTATION: DOSE is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/DOSE.html). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: [email protected] or [email protected].
Guangchuang Yu, Li-Gen Wang, Guang-Rong Yan, Qing-Yu He
Bioinform.2