Many thanks, Tom.
I watched your lots of "youtube". It is great to learn and use ChimeraX. I tried unifold.ipynb (online), but, un-luck, failed several times with paid program. Interestingly, I failed several times to use alphafold2.ipynb (online); but I used ChimeraX with Alphafold successfully for complex prediction. 
In addition, I was told that RoseTTAFold (Linux) could use for complex prediction. I am installing RoseTTAFold in Linux. Again, I filed several times to use RoseTTAFold.ipynb (online). Actually, I do not understand why I always filed to use AlphaFold or RoseTTAFold online (.ipynb with the paid program, Pro+).
Thank you again.
Have a great day!
Roger
Roger Leng, 
Faculty of Medicine,
University of Alberta,
Canada

On Wed, Apr 12, 2023 at 4:05 PM Tom Goddard <goddard@sonic.net> wrote:
Hi Roger,

  Unifold looks interesting.

https://github.com/dptech-corp/Uni-Fold

It is an open source reimplementation of AlphaFold using the PyTorch machine learning framework done by a China-based company called DPTech (https://www.dptech.com/).  From reading the github page it sounds like one of its main advantages over AlphaFold is that the training code and protocol is all open source.  Code for the training of AlphaFold was never made available as far as I know.

  That is all nice, but what are the best reasons for our UCSF lab to try to offer this in ChimeraX?  The ChimeraX AlphaFold user interface took about 2 months of development with ongoing maintenance.  I'd estimate the cost so far at $30,000.  ChimeraX is funded by NIH grants.  Is it worth expending similar resources to implement and maintain an interface to UniFold?

Tom


On Apr 12, 2023, at 2:24 PM, Roger Leng via ChimeraX-users <chimerax-users@cgl.ucsf.edu> wrote:

Dear Administrators,

Is it possible to add "unifold" in your prediction, just like Alphafold?

Thank you.

Sincerely,

Roger Leng
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