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Douyue Li

dblp:425/4546 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
0009-0006-8432-6164ORCID · 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 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › functional genomics
functional enrichment analysis
0.812024
ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities · Bioinform. 2024
Bioinformatics and computational biology › omics data analysis
multi-omics analysis
0.812024
ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities · Bioinform. 2024
Bioinformatics and computational biology
transcriptomics
0.812024
ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities · Bioinform. 2024
Bioinformatics and computational biology › biomarker discovery
cancer biomarker discovery
0.212024
ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities · Bioinform. 2024
Bioinformatics and computational biology
cancer genomics
0.212024
ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities · Bioinform. 2024

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

weighted gene co-expression network analysis · 0.8feature selection · 0.8
YearPublicationVenuePosition
2024 ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities
abstract
MOTIVATION: High-throughput technologies yield a broad spectrum of multi-omics datasets, which offer unparalleled insights into complex biological systems. However, effectively analyzing this diverse array of data presents challenges, considering factors such as species diversity, data types, costs, and limitations of the available tools. RESULTS: Herein, we present ExpOmics, a comprehensive web platform featuring 7 applications and 4 toolkits, with 28 customizable analysis functions spanning various analyses of differential expression, co-expression, Weighted Gene Co-expression Network Analysis (WGCNA), feature selection, and functional enrichment. ExpOmics allows users to upload and explore multi-omics data without organism restrictions, supporting various expression data, including genes, mRNAs, lncRNAs, miRNAs, circRNAs, piRNAs, and proteins and is compatible with diverse gene nomenclatures and expression values. Moreover, ExpOmics enables users to analyze 22 427 transcriptomic datasets of 196 cancer subtypes sourced from 63 projects of The Cancer Genome Atlas Program (TCGA) to identify cancer biomarkers. The analysis results from ExpOmics are presented in high-quality graphical formats suitable for publication and are available for free download. A case study using ExpOmics identified two potential oncogenes, SERPINE1 and SLC43A1, that may regulate colorectal cancer through distinct biological processes. In summary, ExpOmics can serves as a robust platform for global researchers to explore multi-omics data, gain biological insights, and formulate testable hypotheses. AVAILABILITY AND IMPLEMENTATION: ExpOmics is available at http://www.biomedical-web.com/expomics.
Douyue Li, Zhuochao Min, Yubin Chen
Bioinform.1