Related Experiment Video
Updated: Jun 19, 2026

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
Published on: October 11, 2019
Survival Online: a web-based service for the analysis of correlations between gene expression and clinical and
Luca Corradi1, Valentina Mirisola, Ivan Porro
1University of Genoa, Department of Communication, Computer and System Sciences, Viale Causa 13, Genoa, Italy. luca.corradi@unige.it
Background:
Complex microarray gene expression datasets can be used for many independent analyses and are particularly interesting for the validation of potential biomarkers and multi-gene classifiers. This article presents a novel method to perform correlations between microarray gene expression data and clinico-pathological data through a combination of available and newly developed processing tools.
Results:
We developed Survival Online (available at http://ada.dist.unige.it:8080/enginframe/bioinf/bioinf.xml), a Web-based system that allows for the analysis of Affymetrix GeneChip microarrays by using a parallel version of dChip. The user is first enabled to select pre-loaded datasets or single samples thereof, as well as single genes or lists of genes. Expression values of selected genes are then correlated with sample annotation data by uni- or multi-variate Cox regression and survival analyses. The system was tested using publicly available breast cancer datasets and GO (Gene Ontology) derived gene lists or single genes for survival analyses.
Conclusion:
The system can be used by bio-medical researchers without specific computation skills to validate potential biomarkers or multi-gene classifiers. The design of the service, the parallelization of pre-processing tasks and the implementation on an HPC (High Performance Computing) environment make this system a useful tool for validation on several independent datasets.
More Related Videos
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
09:08Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
Related Concept Videos
Cancer Survival Analysis
Comparing the Survival Analysis of Two or More Groups
Assumptions of Survival Analysis
Statistical Software for Data Analysis and Clinical Trials
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Kaplan-Meier Approach