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

Modified on Wed, 27 Nov, 2024 at 3:20 PM

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 [email protected].
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

You are welcome to publish results obtained from DISGENET in scientific publications, provided you cite our most recent publication:
Janet Piñero, Juan Manuel Ramírez-Anguita, Josep Saüch-Pitarch, Francesco Ronzano, Emilio Centeno, Ferran Sanz, Laura I Furlong, The DisGeNET knowledge platform for disease genomics: 2019 update, Nucleic Acids Research, Volume 48, Issue D1, 08 January 2020, Pages D845 –  D855, https://doi.org/10.1093/nar/gkz1021.

Was this article helpful?

That’s Great!

Thank you for your feedback

Sorry! We couldn't be helpful

Thank you for your feedback

Let us know how can we improve this article!

Select at least one of the reasons
CAPTCHA verification is required.

Feedback sent

We appreciate your effort and will try to fix the article