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Foldit Lab Report #11: Deep Learning

Details of a new research paper that Foldit players contributed to! In it, scientists at the University of Washington and at Harvard developed a new, machine-learning based method for protein design. Watch our latest lab report for more.

- How did Foldit help with the new deep learning paper?

- Coronavirus binders & anti-inflammatory design
- More symmetric design, and the problem of aggregation

- NinjaGreg made a sweet symmetric trimer!
See for yourself in the Design of the Month sandbox puzzle!

(Sat, 08/01/2020 - 13:20  |  4 comments)

New blog post walk-through of research paper

See the blog for a walk-through of new research about energy landscape optimization!

Researchers used the work of Foldit players to help develop a new method for protein design. Due to their contributions, Foldit players will be listed as authors on the paper. The new blog post reviews the main points of the paper, but you can read a full pre-print here.

(Fri, 07/31/2020 - 21:39  |  0 comments)

Newsletter July 24: A Good Week for Go Science

Hey Folders! Missed the latest newsletter? Check it out on our blog here. Don't forget to sign up for the mailing list to receive weekly updates about Foldit!

(Wed, 07/29/2020 - 18:55  |  0 comments)

Foldit Newsletter July 17: Bonjour Encore Triple Hélice

Hey folders! Missed the latest newsletter? Check it out on our blog here. Don't forget to sign up for the mailing list here to receive weekly updates about Foldit!

(Fri, 07/24/2020 - 03:49  |  0 comments)

Join the author list on an upcoming research paper

Researchers at the Baker Lab have recently used Foldit players' work to help develop a new method for designing proteins. They are preparing a research paper to share the results, and contributing Foldit players can opt to be included as authors of the paper.

If you played any "Monomer Design" puzzles between 2009 and 2019, and you would like to be included among the authors of the paper, please fill out this Google form.

(Fri, 07/17/2020 - 00:48  |  11 comments)
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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, RosettaCommons