For AI agents: a documentation index is available at the root level at /llms.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
This page is for MSA Search, version 1.0.0.
For other versions, use one of these documentation indexes:
- 2.6.0 (Latest) (default): https://docs.nvidia.com/nim/bionemo/msa-search/2.6.0/llms.txt
- 2.5.0: https://docs.nvidia.com/nim/bionemo/msa-search/2.5.0/llms.txt
- 2.4.0: https://docs.nvidia.com/nim/bionemo/msa-search/2.4.0/llms.txt
- 2.3.0: https://docs.nvidia.com/nim/bionemo/msa-search/2.3.0/llms.txt
- 2.2.0: https://docs.nvidia.com/nim/bionemo/msa-search/2.2.0/llms.txt
- 2.1.0: https://docs.nvidia.com/nim/bionemo/msa-search/2.1.0/llms.txt
- 2.0.0: https://docs.nvidia.com/nim/bionemo/msa-search/2.0.0/llms.txt
- 1.0.0: https://docs.nvidia.com/nim/bionemo/msa-search/1.0.0/llms.txt
This is the first release of MSA Search NIM. MSA Search enables accurate protein structure
prediction from an input protein sequence by predicting potential structural similarities
with previously-observed proteins.
This NIM is not a deep learning model but makes use of NVIDIA GPUs and software libraries for
accelerated multiple sequence alignment. The NIM relies on GPU-accelerated MMSeqs2 to provide
fast, accurate sequence database search and multiple sequence alignment.
