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Related Experiment Video

Updated: Jun 17, 2025

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

The MPLEx Protocol for Multi-omic Analyses of Soil Samples

Published on: May 30, 2018

ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities.

Douyue Li¹, Zhuochao Min², Jia Guo¹

¹The Key Laboratory of Advanced Interdisciplinary Studies, The First Affiliated Hospital of Guangzhou Medical University, GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Medical University, Guangzhou 510182, People's Republic of China.

Bioinformatics (Oxford, England)

|August 11, 2024

Summary

ExpOmics is a web platform for analyzing multi-omics data, overcoming challenges in species diversity and data types. It aids researchers in exploring complex biological systems and identifying potential cancer biomarkers.

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Last Updated: Jun 17, 2025

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Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

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Published on: March 5, 2022

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

High-throughput technologies generate vast multi-omics datasets for biological insights.
Analyzing diverse multi-omics data faces challenges like species variation, data types, cost, and tool limitations.

Purpose of the Study:

To introduce ExpOmics, a comprehensive web platform designed for multi-omics data analysis.
To provide researchers with a versatile tool for exploring gene expression, co-expression, network analysis, and functional enrichment across various organisms.

Main Methods:

Developed ExpOmics, a web platform with 7 applications and 4 toolkits offering 28 customizable analysis functions.
Integrated analysis of differential expression, co-expression, Weighted Gene Co-expression Network Analysis (WGCNA), feature selection, and functional enrichment.
Enabled organism-agnostic multi-omics data exploration, supporting diverse data types (genes, mRNAs, lncRNAs, miRNAs, circRNAs, piRNAs, proteins) and nomenclatures.

Main Results:

ExpOmics facilitates the analysis of 22,427 transcriptomic datasets from The Cancer Genome Atlas Program (TCGA) for cancer biomarker discovery.
Results are presented in publication-quality graphical formats and are freely downloadable.
A case study identified SERPINE1 and SLC43A1 as potential oncogenes regulating colorectal cancer.

Conclusions:

ExpOmics serves as a robust, free platform for global researchers to analyze multi-omics data.
The platform empowers users to gain biological insights and generate testable hypotheses.
ExpOmics supports diverse biological research by overcoming common multi-omics analysis hurdles.