Do I need a commercial license? Can I use DISGENET data in my product?

This article clarifies the distinction between commercial and non-commercial use of DISGENET, explains licensing options, and provides information on data redistribution.

Non-Commercial Use

A Free Academic License for DISGENET is intended for purely academic purposes.

This includes not-for-profit research, teaching activities delivered by academic institutions, and scientific research work without any direct or indirect commercial purpose.

If you incorporate DISGENET data into other works, please ensure proper citation including version number (see below) and that your derived work complies with the restrictions defined in the DISGENET Subscription Agreement.

Commercial Use

A commercial license is required if you belong to a commercial company wishing to use DISGENET in any capacity.

If you are an organization conducting research for a commercial product (existing or in development) or using DISGENET to enhance a commercial product or service (even if free), a commercial license is required.

If you are unsure about your use case, please contact us at info@disgenet.com.

Can I redistribute DISGENET data?

Our standard licenses do not allow redistributing or reselling the entire database or a portion of it. This applies to both the whole dataset and any part of it.

If you are interested in repackaging DISGENET data for commercial purposes, please contact us to discuss a custom licensing agreement.

Am I allowed to use DISGENET data in products I intend to sell?

No, our licenses do not allow using or incorporating the DISGENET database, or any part of it, in products for resale. This includes both the full dataset and any portion of it.

Publishing research & citing DISGENET

If you use DISGENET in your work, please cite our URL https://www.disgenet.com and our latest publication:

DISGENET: Accelerating Data-Driven Discovery in Disease Genomics and Therapeutic Development.

Janet Piñero, Javier Corvi, Natalia Rykova, Anna Guillem, Amelia Martinez, Jaione Telleria Zufiaur, Ivo Rivetta, Sarah Holmes, Mariandrea Del Boccio, Daniel Shapoval, Macarena de Sarasqueta Szneiderowicz, Felix Slager, Ferran Sanz, Laura I Furlong.

doi: https://doi.org/10.64898/2026.01.05.697749