Description

The Continuous Automated Model EvaluatiOn (CAMEO) is a weekly, fully automated blind benchmarking experiment of three-dimensional protein prediction servers.

The www.cameo3d.org website displays the results of the experiment for "public" servers. Registered users participating in the experiment can in addition access to the results of "development" servers.

Liability disclaimer

• The CAMEO service is provided “as is”. In no event shall CAMEO or its developers be liable for any consequential, special, incidental, or indirect damages of any kind arising out of the use of CAMEO or its results.
• CAMEO is not responsible for any problems on your server. This includes overloading the system or any other technical problems.
• CAMEO will publicly display the results of your service in the context of other results and will apply computational tools on the results provided by your server, including, but not limited to, structure and model comparison tools and model quality assessment.
• CAMEO reserves the right to exclude services with continued technical problems, low availability, or format problems.

Terms

• When publishing any results obtained from the CAMEO server, you agree to cite the appropriate references (see the bottom of this page).
• Evaluation of “development” servers is provided exclusively for development purposes. You acknowledge that such results can only be published after marking the complete dataset as “public” on CAMEO.
• You confirm that all predictions provided by your server to CAMEO can be redistributed under the CC BY-SA 4.0 Creative Commons Attribution-ShareAlike 4.0 International License (see below)

Copyright

The data provided by CAMEO is licensed under the CC BY-SA 4.0 Creative Commons Attribution-ShareAlike 4.0 International License, i.e. you can copy and redistribute the models in any medium or format, transform and build upon the models for any purpose, even commercially, under the following terms:

• Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. When you publish, patent or distribute results that were fully or partially based on models obtained from CAMEO, please cite the corresponding papers (see below).
• ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
• No additional restrictions — you may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

This is a human-readable summary of (and not a substitute for) the CC BY-SA 4.0 license.

Privacy Notice

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References

When publishing any results obtained from the CAMEO server or its data, you agree to cite the appropriate references:

1. Leemann M., Sagasta S., Eberhardt J., Schwede T., Robin X., Durairaj J. Automated benchmarking of combined protein structure and ligand conformation prediction. Proteins. (2023), 91 1912–1924. [DOI: 10.1002/prot.26605]
2. Robin X., Haas J., Gumienny R., Smolinski A., Tauriello G., Schwede T. Continuous Automated Model EvaluatiOn (CAMEO)—Perspectives on the future of fully automated evaluation of structure prediction methods. Proteins. (2021), 89, 1977-1986. [DOI: 10.1002/prot.26213]
3. Haas J., Gumienny R., Barbato A., Ackermann F., Tauriello G., Bertoni M., Studer G., Smolinski A., Schwede T. Introducing "best single template" models as reference baseline for the Continuous Automated Model Evaluation (CAMEO). Proteins. (2019), 87, 1378-1387. [DOI: 10.1002/prot.25815]
4. Haas J., Barbato A., Behringer D., Studer G., Roth S., Bertoni M., Mostaguir K., Gumienny R., Schwede T. Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12. Proteins. (2018), 86, 387-398. [DOI: 10.1002/prot.25431]
5. Haas J., Roth S., Arnold K., Kiefer F., Schmidt T., Bordoli L. and Schwede T.(2013). The Protein Model Portal - a comprehensive resource for protein structure and model information. Database [PMID: 23624946].