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Download code/standard.py from HUBioDataLab/ASCARIS: direct link, hf CLI and curl.
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https://huggingface.co/spaces/HUBioDataLab/ASCARIS/resolve/ab6e7473f055f745aad64f21a62b00a67de580dd/code/standard.py
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hf download hf://spaces/HUBioDataLab/ASCARIS@ab6e7473f055f745aad64f21a62b00a67de580dd/code/standard.py
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curl -L -o standard.py https://huggingface.co/spaces/HUBioDataLab/ASCARIS/resolve/ab6e7473f055f745aad64f21a62b00a67de580dd/code/standard.py
820 Bytes
| def standardize(df, get_columns): | |
| cols_to_change = ['sasa', 'domaindistance3D', 'disulfide', 'intMet', 'intramembrane', | |
| 'naturalVariant', 'dnaBinding', 'activeSite', 'nucleotideBinding', | |
| 'lipidation', 'site', 'transmembrane', 'crosslink', 'mutagenesis', | |
| 'strand', 'helix', 'turn', 'metalBinding', 'repeat', 'caBinding', | |
| 'topologicalDomain', 'bindingSite', 'region', 'signalPeptide', | |
| 'modifiedResidue', 'zincFinger', 'motif', 'coiledCoil', 'peptide', | |
| 'transitPeptide', 'glycosylation', 'propeptide'] | |
| for col in cols_to_change: # because in the other ones, they are 3D distance. Here, no distance calculated. | |
| df[col] = 'nan' | |
| df = df[get_columns.columns] | |
| return df | |