protein-structure
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I've implemented low-memory attention (9670958) using an algorithm from a recent preprint (https://arxiv.org/pdf/2112.05682.pdf), enhanced a little bit with the ability to add multiple biases + batch dimensions. Lacking the JAX map & scan used in the original implementation, which I've had to replace with for loops, ours is quite a bit slower (exact figures depend heavily on the choice of chunk si
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Hey,
I would propose extend list of available models by SeqVec (ELMo-based implementation) which was presented in the Modeling aspects of the language of life through transfer-learning protein sequences paper.
SeqVec model trained on UniRef50 is available at: [SeqVec-model](
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Describe the solution you'd like
- inputs for chain selection as a separate .txt file
- Input as list of PDB codes (txt file) rather than PDB directory path
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This issue is a roadmap for Molly.jl development. Feel free to discuss things here or submit a PR. Bear in mind that significant refactoring will probably occur as the package develops.
Low hanging fruit
Want to get involved? These issues might be the place to start:
- Speedups to the code. Both on the level of individual functions and the overall algorithm. [Getting there]
- Look over
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I encountered this error when running Equibind.
/opt/dgl/src/runtime/tensordispatch.cc:43: TensorDispatcher: dlopen failed: libtorch_cuda.so: cannot open shared object file: No such file or directory
According to this https://discuss.dgl.ai/t/error-tensordispatcher/2468 the error impacts performance but does not impact usage. Equibind appears to run in spite of this error. I thought you m
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See https://github.com/biopython/biopython/blob/master/Bio/SeqFeature.py and
__add__, need to do the same specifically for integer offsets.Workaround
feature + (-5)instead offeature - 5, see https://twitter.com/tomeraltman/status/1473764959347638273