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Related Experiment Video

Updated: Aug 2, 2025

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal

Published on: October 11, 2019

Genealyzer: web application for the analysis and comparison of gene expression data.

Kristina Lietz¹, Babak Saremi¹, Lena Wiese^2,3

¹Research Group Bioinformatics, Fraunhofer ITEM, Hannover, Germany.

BMC Bioinformatics

|April 18, 2023

Summary

This summary is machine-generated.

This study introduces Genealyzer, a web application simplifying microarray data analysis for reproducible research. It enables comparison of gene expression data across different technologies and organisms, unlocking insights from diverse datasets.

Keywords:

Gene expression Microarray Webapplication

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Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

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Published on: July 29, 2022

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Gene expression profiling is crucial for drug development and functional gene analysis.
Microarray data is abundant but often difficult to compare due to varying technologies.
Existing data challenges hinder large-scale reproducibility studies.

Purpose of the Study:

To present a user-friendly web application for analyzing microarray data.
To enable convenient and customizable analysis for large-scale reproducibility.
To facilitate comparison of data from different technologies and organisms.

Main Methods:

Development of a web application abstracting complex mathematical and programmatic details.
Implementation of differential gene expression analysis, Gene Ontology (GO) enrichment analysis, and result comparison.
Support for Affymetrix, one-channel, and two-channel Agilent microarray data.

Main Results:

The application provides a unified platform for microarray data analysis.
All analysis steps are visualized with meaningful plots for intuitive operation.
Genealyzer handles diverse data types and offers flexible analysis.

Conclusions:

The web application facilitates comparison of results across different technologies and organisms.
It enhances data reproducibility and enables new insights from existing study data.
Genealyzer offers a powerful tool for exploring diverse microarray datasets.