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Merge pull request #652 from lbarraga/alphafold-typos
typo fixes in alphafold md
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mkdocs/docs/HPC/alphafold.md

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@@ -96,9 +96,9 @@ export ALPHAFOLD_DATA_DIR={{directory}}/{{version}}
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### Running AlphaFold
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AlphaFold provides run script called [run_alphafold.py](https://raw.githubusercontent.com/deepmind/alphafold/main/run_alphafold.py)
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AlphaFold provides a script called [run_alphafold.py](https://raw.githubusercontent.com/deepmind/alphafold/main/run_alphafold.py)
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A symbolic link named *alphafold* that points to the this script is included,
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A symbolic link named *alphafold* that points to this script is included,
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so you can just use `alphafold` instead of `run_alphafold.py` or `python run_alphafold.py` after loading the AlphaFold module.
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The `run_alphafold.py` script has also been slightly modified such that defining the `$ALPHAFOLD_DATA_DIR` (see [above](./#setting-up-the-environment)) is sufficient to pick up all the data provided in that location,
@@ -158,7 +158,7 @@ This highlights the difference between CPU and GPU performance even more.
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The following example comes from the official [Examples section]({{readme}}#examples) in the Alphafold [README]({{readme}}).
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The run command is slightly different (see above: [Running AlphaFold](./running-alphafold)).
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Do not forget to setup the environment (see above: [Setting up the environment](./setting-up-the-environment)).
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Do not forget to set up the environment (see above: [Setting up the environment](./setting-up-the-environment)).
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### Folding a monomer
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@@ -193,7 +193,7 @@ The main difference between using a GPU or CPU in a job script is what module to
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For running AlphaFold on GPU, use an AlphaFold module that mentions `CUDA` (or `cuda`),
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for example `AlphaFold/2.3.1-foss-2022a-CUDA-11.7.0`.
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To run the jobs cripts you need to create a file named `T1050.fasta` with the following content:
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To run the job scripts you need to create a file named `T1050.fasta` with the following content:
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```fasta
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>T1050 A7LXT1, Bacteroides Ovatus, 779 residues|

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