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Second, we have partnered with EMBL-EBI to develop the AlphaFold DB. ... (making it freely available for both academic and commercial use).

Data is available for academic and commercial use, under a CC-BY-4.0 license. EMBL-EBI expects attribution (e.g. in publications, services or products) for any of its online services, databases or software in accordance with good scientific practice. If you make use of an AlphaFold prediction, please cite: Jumper, J et al.

AlphaFold DB provides open access to protein structure predictions for ... commercial use under Creative Commons Attribution 4.0 (CC-BY 4.0) license terms.

Data is available for academic and commercial use, under a CC-BY-4.0 license. EMBL-EBI expects attribution (e.g. in publications, services or products) for any of its online services, databases or software in accordance with good scientific practice. If you make use of an AlphaFold prediction, please cite the following papers: Jumper, J et al.

Command: alphafold. AlphaFold is an artificial intelligence method for predicting protein structures that has been highly successful in recent tests. The alphafold command: . finds and retrieves existing models from the AlphaFold Database – freely available for academic and commercial use under CC BY 4.0 runs new predictions with AlphaFold using Google Colab

Note that while the AlphaFold code is licensed under the open source Apache 2.0 License, the AlphaFold parameters are made available for non-commercial use ...

... the structure of many proteins using the sequence of the proteins alone ... Although the source code for AlphaFold 2 is freely available ...

To understand why let's take a quick look at how AlphaFold and ... R&D that is driven more by narrower short-term commercial objectives.

AlphaFold. Protein Structure Database. Developed by DeepMind and EMBL-EBI. Examples: Free fatty acid receptor 2 At1g58602 Q5VSL9 E. coli Help: AlphaFold DB search help. Feedback on structure: Contact alphafold@deepmind.com If you want to share your feedback on an AlphaFold structure prediction, please contact DeepMind by clicking on this button.

How to run AlphaFold on Colab. You will need the 1-letter sequence of your protein (that's all). To access the site, you can use the "AlphaFold2 in CoLab" button in the Phenix GUI or you can go directly to the Phenix AlphaFold Colab notebook. Then you paste your sequence into the form and type in a job name.

Any publication that discloses findings arising from using this notebook should cite the AlphaFold paper. Licenses. This Colab uses the AlphaFold model parameters and its outputs are thus for non-commercial use only, under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.

The model weights are for non commercial use. But what if somebody creates a large database of prefolded proteins? Basically, what is the ...

Tool: AlphaFold. AlphaFold is an artificial intelligence method for predicting protein structures that has been highly successful in recent tests. The ChimeraX AlphaFold tool: . finds and retrieves existing models from the AlphaFold Database – freely available for academic and commercial use under CC BY 4.0 runs new predictions with AlphaFold using Google Colab

Licensed works, modifications, and larger works may be distributed under different terms and without source code. Permissions. Commercial use; Modification ...

How to run AlphaFold on Colab. You will need the 1-letter sequence of your protein (that's all). To access the site, you can use the "AlphaFold2 in CoLab" button in the Phenix GUI or you can go directly to the Phenix AlphaFold Colab notebook. Then you paste your sequence into the form, go to the pull-down menu item "Runtime" and select "Run all".

This means, for example, that David Baker licenses Rosetta for free to academic and government, but commercial users have to obtain a paid commercial license.