microsoft / microsoft/foldingdiff
Conditional generation
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- Dominant language
- Jupyter Notebook
- Stars
- 568
- Forks
- 74
- Avg merge
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- Merged PRs (30d)
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Description
Thanks to the author for sharing, this is the wonderful work.
I'd like to ask you a question. I want to achieve the conditional generation of the three-dimensional structure of the protein. For example, input the target protein amino acid sequence, generate the corresponding amino acid sequence of the protein three-dimensional structure. Can condition generation be realized by modifying Foldingdiff? Can you briefly explain how to modify it? I would appreciate it if you could give me some help.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue does not name any files, tests, or entry points. Start by reading the FoldingDiff implementation and documentation to determine whether conditioning on an amino acid sequence is supported; the requested changes and completion criteria are not defined.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- bioinformatics, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100