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Related Experiment Video

Updated: Jul 19, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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Published on: December 7, 2021

Lessons learned to boost a bioinformatics knowledge base reusability, the Bgee experience.

Tarcisio Mendes de Farias^1,2, Julien Wollbrett^1,2, Marc Robinson-Rechavi^1,2

¹SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.

|August 17, 2023

Summary

This summary is machine-generated.

Improving bioinformatics knowledge base interoperability is key for data reuse and biomedical research ROI. This study offers pragmatic methods and lessons learned to enhance knowledge base utility and value.

Keywords:

data reusability databases interoperability ontologies

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Area of Science:

Bioinformatics
Biomedical Research
Data Science

Background:

Interoperability of bioinformatics knowledge bases is crucial for maximizing data reusability and return on investment in biomedical research.
Knowledge bases offer value when reused, but lack of interoperability limits their utility.
Enhancing data exchange and integration is a high-priority requirement for life science research.

Purpose of the Study:

To discuss approaches for boosting interoperability in bioinformatics knowledge bases.
To provide pragmatic methods and transferable skills for promoting knowledge base reusability.
To highlight the importance of interoperability for unlocking the full potential of bioinformatics data.

Main Methods:

Analysis of real-world scenario examples, primarily from the Bgee gene expression knowledge base.
Comparison of Bgee's interoperability experiences with implementations in other major bioinformatics knowledge bases.
Identification and discussion of ten general lessons learned applicable to any bioinformatics knowledge base.

Main Results:

Several approaches to enhance interoperability based on specific components are presented.
Real-world examples from Bgee demonstrate practical applications of interoperability strategies.
Similar implementations in other leading bioinformatics knowledge bases confirm the transferability of findings.

Conclusions:

The study provides pragmatic methods and transferable skills to enhance the reusability of bioinformatics knowledge bases.
Focusing on interoperability is essential for increasing the utility and value of these resources.
The lessons learned can guide efforts to foster data reuse across the bioinformatics landscape.