Luang Xu

dblp:291/0076 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · unresolved

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

Applied, interdisciplinary, general and emerging computing · 1 · 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
proteomics
0.512021
ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets · Bioinform. 2021
Bioinformatics and computational biology › proteomics
quantitative proteomics
0.512021
ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets · Bioinform. 2021

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

r shiny · 0.5docker · 0.5
YearPublicationVenuePosition
2021 ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets
abstract
SUMMARY: The rapid progresses of high-throughput sequencing technology-based omics and mass spectrometry-based proteomics, such as data-independent acquisition and its penetration to clinical studies have generated increasing number of proteomic datasets containing hundreds to thousands of samples. To analyze these quantitative proteomic datasets and other omics (e.g. transcriptomics and metabolomics) datasets more efficiently and conveniently, we present a web server-based software tool ProteomeExpert implemented in Docker, which offers various analysis tools for experimental design, data mining, interpretation and visualization of quantitative proteomic datasets. ProteomeExpert can be deployed on an operating system with Docker installed or with R language environment. AVAILABILITY AND IMPLEMENTATION: The Docker image of ProteomeExpert is freely available from https://hub.docker.com/r/lifeinfo/proteomeexpert. The source code of ProteomeExpert is also openly accessible at http://www.github.com/guomics-lab/ProteomeExpert/. In addition, a demo server is provided at https://proteomic.shinyapps.io/peserver/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Tiansheng Zhu, Xishan Yan, Zhicheng Wu, Xiaoxu Zhou, Weigang Ge, Luang Xu, Guan Ruan, Zhangzhi Xue, Guo-Bo Chen, Tiannan Guo
Bioinform.10