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Related Experiment Video

Updated: Jun 12, 2026

Metabolic Mapping: Quantitative Enzyme Cytochemistry and Histochemistry to Determine the Activity of Dehydrogenases in Cells and Tissues

Metabolic Mapping: Quantitative Enzyme Cytochemistry and Histochemistry to Determine the Activity of Dehydrogenases in Cells and Tissues

Published on: May 26, 2018

Large-scale benchmark of Endeavour using MetaCore maps.

Sven Schuierer¹, Léon-Charles Tranchevent, Uwe Dengler

¹Novartis Pharma AG, Postfach, Basel, Switzerland. sven.schuierer@novartis.com

Bioinformatics (Oxford, England)

|June 12, 2010

Summary

Endeavour is a novel tool that prioritizes candidate genes for biological pathways and diseases by integrating multiple genomic data sources. It demonstrates high accuracy in identifying promising genes, aiding research in these areas.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Gene prioritization is crucial for understanding biological processes and diseases.
Existing methods may not effectively integrate diverse genomic data sources.

Purpose of the Study:

To introduce Endeavour, a tool for identifying promising candidate genes.
To evaluate Endeavour's performance in prioritizing genes for biological pathways and diseases.

Main Methods:

Endeavour integrates multiple genomic data sources.
Benchmarking utilized 450 pathway maps and 826 disease marker sets from MetaCore.
Performance was assessed using receiver operating characteristic (ROC) curves.

Main Results:

Endeavour achieved an area under the ROC curve of 0.97 for pathway gene sets.
Endeavour achieved an area under the ROC curve of 0.91 for disease gene sets.
The tool efficiently prioritizes candidate genes.

Conclusions:

Endeavour effectively detects promising genes from large candidate lists.
The tool's performance indicates its utility for prioritizing genes related to pathways and diseases.
Endeavour facilitates efficient gene prioritization in genomic research.