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Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 7 new columns ({'molecule_chembl_id', 'NumHDonors', 'NumHAcceptors', 'canonical_smiles', 'MW', 'bioactivity_class', 'LogP'}) and 881 missing columns ({'PubchemFP191', 'PubchemFP241', 'PubchemFP341', 'PubchemFP356', 'PubchemFP113', 'PubchemFP690', 'PubchemFP305', 'PubchemFP418', 'PubchemFP472', 'PubchemFP275', 'PubchemFP518', 'PubchemFP18', 'PubchemFP74', 'PubchemFP551', 'PubchemFP541', 'PubchemFP568', 'PubchemFP378', 'PubchemFP334', 'PubchemFP590', 'PubchemFP742', 'PubchemFP419', 'PubchemFP167', 'PubchemFP145', 'PubchemFP537', 'PubchemFP781', 'PubchemFP493', 'PubchemFP138', 'PubchemFP556', 'PubchemFP112', 'PubchemFP593', 'PubchemFP318', 'PubchemFP304', 'PubchemFP282', 'PubchemFP409', 'PubchemFP802', 'PubchemFP80', 'PubchemFP675', 'PubchemFP454', 'PubchemFP480', 'PubchemFP310', 'PubchemFP476', 'PubchemFP386', 'PubchemFP11', 'PubchemFP343', 'PubchemFP93', 'PubchemFP863', 'PubchemFP865', 'PubchemFP166', 'PubchemFP129', 'PubchemFP817', 'PubchemFP326', 'PubchemFP149', 'PubchemFP733', 'PubchemFP706', 'PubchemFP586', 'PubchemFP792', 'PubchemFP223', 'PubchemFP370', 'PubchemFP604', 'PubchemFP391', 'PubchemFP281', 'PubchemFP815', 'PubchemFP81', 'PubchemFP165', 'PubchemFP415', 'PubchemFP95', 'PubchemFP203', 'PubchemFP211', 'PubchemFP277', 'PubchemFP861', 'PubchemFP805', 'PubchemFP243', 'PubchemFP132', 'PubchemFP363', 'PubchemFP547', 'PubchemFP76', 'PubchemFP543', 'PubchemFP524', 'PubchemFP3', 'PubchemFP103', 'PubchemFP844', 'PubchemFP33', 'PubchemFP855', 'PubchemFP673', 'PubchemFP306', 'PubchemFP176', 'PubchemFP743', 'PubchemFP5', 'PubchemFP745', 'PubchemFP158', 'PubchemFP316', 'PubchemFP484', 'PubchemFP499', 'PubchemFP498', 'Pubchem ... chemFP622', 'PubchemFP184', 'PubchemFP853', 'PubchemFP250', 'PubchemFP331', 'PubchemFP171', 'PubchemFP375', 'PubchemFP396', 'PubchemFP747', 'PubchemFP522', 'PubchemFP487', 'PubchemFP714', 'PubchemFP350', 'PubchemFP583', 'PubchemFP558', 'PubchemFP574', 'PubchemFP385', 'PubchemFP687', 'PubchemFP572', 'PubchemFP533', 'PubchemFP233', 'PubchemFP60', 'PubchemFP420', 'PubchemFP649', 'PubchemFP359', 'PubchemFP616', 'PubchemFP548', 'PubchemFP397', 'PubchemFP528', 'PubchemFP647', 'PubchemFP740', 'PubchemFP570', 'PubchemFP674', 'PubchemFP232', 'PubchemFP59', 'PubchemFP254', 'PubchemFP753', 'PubchemFP90', 'PubchemFP878', 'PubchemFP49', 'PubchemFP57', 'PubchemFP66', 'PubchemFP352', 'PubchemFP437', 'PubchemFP588', 'PubchemFP342', 'PubchemFP795', 'PubchemFP0', 'PubchemFP613', 'PubchemFP287', 'PubchemFP295', 'PubchemFP377', 'PubchemFP660', 'PubchemFP188', 'PubchemFP851', 'PubchemFP852', 'PubchemFP58', 'PubchemFP860', 'PubchemFP535', 'PubchemFP381', 'PubchemFP637', 'PubchemFP725', 'PubchemFP786', 'PubchemFP520', 'PubchemFP442', 'PubchemFP4', 'PubchemFP459', 'PubchemFP596', 'PubchemFP351', 'PubchemFP193', 'PubchemFP552', 'PubchemFP44', 'PubchemFP727', 'PubchemFP179', 'PubchemFP843', 'PubchemFP592', 'PubchemFP809', 'PubchemFP189', 'PubchemFP641', 'PubchemFP741', 'PubchemFP658', 'PubchemFP99', 'PubchemFP629', 'PubchemFP808', 'PubchemFP666', 'PubchemFP290', 'PubchemFP671', 'PubchemFP87', 'PubchemFP45', 'PubchemFP160', 'PubchemFP234', 'PubchemFP763', 'PubchemFP471', 'PubchemFP446', 'PubchemFP286'}). This happened while the csv dataset builder was generating data using hf://datasets/DanielShunom/ubiquitin-l1-hydrolase-bioactivity/UBQTN_processed_allBioactivity.csv (at revision f960ca47b2a3d802c43851725f73d8c0b81b945e) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2292, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast molecule_chembl_id: string canonical_smiles: string bioactivity_class: string MW: double LogP: double NumHDonors: double NumHAcceptors: double pIC50: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1238 to {'PubchemFP0': Value(dtype='int64', id=None), 'PubchemFP1': Value(dtype='int64', id=None), 'PubchemFP2': Value(dtype='int64', id=None), 'PubchemFP3': Value(dtype='int64', id=None), 'PubchemFP4': Value(dtype='int64', id=None), 'PubchemFP5': Value(dtype='int64', id=None), 'PubchemFP6': Value(dtype='int64', id=None), 'PubchemFP7': Value(dtype='int64', id=None), 'PubchemFP8': Value(dtype='int64', id=None), 'PubchemFP9': Value(dtype='int64', id=None), 'PubchemFP10': Value(dtype='int64', id=None), 'PubchemFP11': Value(dtype='int64', id=None), 'PubchemFP12': Value(dtype='int64', id=None), 'PubchemFP13': Value(dtype='int64', id=None), 'PubchemFP14': Value(dtype='int64', id=None), 'PubchemFP15': Value(dtype='int64', id=None), 'PubchemFP16': Value(dtype='int64', id=None), 'PubchemFP17': Value(dtype='int64', id=None), 'PubchemFP18': Value(dtype='int64', id=None), 'PubchemFP19': Value(dtype='int64', id=None), 'PubchemFP20': Value(dtype='int64', id=None), 'PubchemFP21': Value(dtype='int64', id=None), 'PubchemFP22': Value(dtype='int64', id=None), 'PubchemFP23': Value(dtype='int64', id=None), 'PubchemFP24': Value(dtype='int64', id=None), 'PubchemFP25': Value(dtype='int64', id=None), 'PubchemFP26': Value(dtype='int64', id=None), 'PubchemFP27': Value(dtype='int64', id=None), 'PubchemFP28': Value(dtype='int64', id=None), 'PubchemFP29': Value(dtype='int64', id=None), 'PubchemFP30': Value(dtype='int64', id=None), 'PubchemFP31': Value(dtype='int64', id=None), 'PubchemFP32': Value(dtype='int64', i ... , 'PubchemFP850': Value(dtype='int64', id=None), 'PubchemFP851': Value(dtype='int64', id=None), 'PubchemFP852': Value(dtype='int64', id=None), 'PubchemFP853': Value(dtype='int64', id=None), 'PubchemFP854': Value(dtype='int64', id=None), 'PubchemFP855': Value(dtype='int64', id=None), 'PubchemFP856': Value(dtype='int64', id=None), 'PubchemFP857': Value(dtype='int64', id=None), 'PubchemFP858': Value(dtype='int64', id=None), 'PubchemFP859': Value(dtype='int64', id=None), 'PubchemFP860': Value(dtype='int64', id=None), 'PubchemFP861': Value(dtype='int64', id=None), 'PubchemFP862': Value(dtype='int64', id=None), 'PubchemFP863': Value(dtype='int64', id=None), 'PubchemFP864': Value(dtype='int64', id=None), 'PubchemFP865': Value(dtype='int64', id=None), 'PubchemFP866': Value(dtype='int64', id=None), 'PubchemFP867': Value(dtype='int64', id=None), 'PubchemFP868': Value(dtype='int64', id=None), 'PubchemFP869': Value(dtype='int64', id=None), 'PubchemFP870': Value(dtype='int64', id=None), 'PubchemFP871': Value(dtype='int64', id=None), 'PubchemFP872': Value(dtype='int64', id=None), 'PubchemFP873': Value(dtype='int64', id=None), 'PubchemFP874': Value(dtype='int64', id=None), 'PubchemFP875': Value(dtype='int64', id=None), 'PubchemFP876': Value(dtype='int64', id=None), 'PubchemFP877': Value(dtype='int64', id=None), 'PubchemFP878': Value(dtype='int64', id=None), 'PubchemFP879': Value(dtype='int64', id=None), 'PubchemFP880': Value(dtype='int64', id=None), 'pIC50': Value(dtype='float64', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1872, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 7 new columns ({'molecule_chembl_id', 'NumHDonors', 'NumHAcceptors', 'canonical_smiles', 'MW', 'bioactivity_class', 'LogP'}) and 881 missing columns ({'PubchemFP191', 'PubchemFP241', 'PubchemFP341', 'PubchemFP356', 'PubchemFP113', 'PubchemFP690', 'PubchemFP305', 'PubchemFP418', 'PubchemFP472', 'PubchemFP275', 'PubchemFP518', 'PubchemFP18', 'PubchemFP74', 'PubchemFP551', 'PubchemFP541', 'PubchemFP568', 'PubchemFP378', 'PubchemFP334', 'PubchemFP590', 'PubchemFP742', 'PubchemFP419', 'PubchemFP167', 'PubchemFP145', 'PubchemFP537', 'PubchemFP781', 'PubchemFP493', 'PubchemFP138', 'PubchemFP556', 'PubchemFP112', 'PubchemFP593', 'PubchemFP318', 'PubchemFP304', 'PubchemFP282', 'PubchemFP409', 'PubchemFP802', 'PubchemFP80', 'PubchemFP675', 'PubchemFP454', 'PubchemFP480', 'PubchemFP310', 'PubchemFP476', 'PubchemFP386', 'PubchemFP11', 'PubchemFP343', 'PubchemFP93', 'PubchemFP863', 'PubchemFP865', 'PubchemFP166', 'PubchemFP129', 'PubchemFP817', 'PubchemFP326', 'PubchemFP149', 'PubchemFP733', 'PubchemFP706', 'PubchemFP586', 'PubchemFP792', 'PubchemFP223', 'PubchemFP370', 'PubchemFP604', 'PubchemFP391', 'PubchemFP281', 'PubchemFP815', 'PubchemFP81', 'PubchemFP165', 'PubchemFP415', 'PubchemFP95', 'PubchemFP203', 'PubchemFP211', 'PubchemFP277', 'PubchemFP861', 'PubchemFP805', 'PubchemFP243', 'PubchemFP132', 'PubchemFP363', 'PubchemFP547', 'PubchemFP76', 'PubchemFP543', 'PubchemFP524', 'PubchemFP3', 'PubchemFP103', 'PubchemFP844', 'PubchemFP33', 'PubchemFP855', 'PubchemFP673', 'PubchemFP306', 'PubchemFP176', 'PubchemFP743', 'PubchemFP5', 'PubchemFP745', 'PubchemFP158', 'PubchemFP316', 'PubchemFP484', 'PubchemFP499', 'PubchemFP498', 'Pubchem ... chemFP622', 'PubchemFP184', 'PubchemFP853', 'PubchemFP250', 'PubchemFP331', 'PubchemFP171', 'PubchemFP375', 'PubchemFP396', 'PubchemFP747', 'PubchemFP522', 'PubchemFP487', 'PubchemFP714', 'PubchemFP350', 'PubchemFP583', 'PubchemFP558', 'PubchemFP574', 'PubchemFP385', 'PubchemFP687', 'PubchemFP572', 'PubchemFP533', 'PubchemFP233', 'PubchemFP60', 'PubchemFP420', 'PubchemFP649', 'PubchemFP359', 'PubchemFP616', 'PubchemFP548', 'PubchemFP397', 'PubchemFP528', 'PubchemFP647', 'PubchemFP740', 'PubchemFP570', 'PubchemFP674', 'PubchemFP232', 'PubchemFP59', 'PubchemFP254', 'PubchemFP753', 'PubchemFP90', 'PubchemFP878', 'PubchemFP49', 'PubchemFP57', 'PubchemFP66', 'PubchemFP352', 'PubchemFP437', 'PubchemFP588', 'PubchemFP342', 'PubchemFP795', 'PubchemFP0', 'PubchemFP613', 'PubchemFP287', 'PubchemFP295', 'PubchemFP377', 'PubchemFP660', 'PubchemFP188', 'PubchemFP851', 'PubchemFP852', 'PubchemFP58', 'PubchemFP860', 'PubchemFP535', 'PubchemFP381', 'PubchemFP637', 'PubchemFP725', 'PubchemFP786', 'PubchemFP520', 'PubchemFP442', 'PubchemFP4', 'PubchemFP459', 'PubchemFP596', 'PubchemFP351', 'PubchemFP193', 'PubchemFP552', 'PubchemFP44', 'PubchemFP727', 'PubchemFP179', 'PubchemFP843', 'PubchemFP592', 'PubchemFP809', 'PubchemFP189', 'PubchemFP641', 'PubchemFP741', 'PubchemFP658', 'PubchemFP99', 'PubchemFP629', 'PubchemFP808', 'PubchemFP666', 'PubchemFP290', 'PubchemFP671', 'PubchemFP87', 'PubchemFP45', 'PubchemFP160', 'PubchemFP234', 'PubchemFP763', 'PubchemFP471', 'PubchemFP446', 'PubchemFP286'}). This happened while the csv dataset builder was generating data using hf://datasets/DanielShunom/ubiquitin-l1-hydrolase-bioactivity/UBQTN_processed_allBioactivity.csv (at revision f960ca47b2a3d802c43851725f73d8c0b81b945e) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PubchemFP0
int64 | PubchemFP1
int64 | PubchemFP2
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int64 | PubchemFP331
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int64 | PubchemFP333
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int64 | PubchemFP341
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int64 | PubchemFP396
int64 | PubchemFP397
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int64 | PubchemFP619
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int64 | PubchemFP674
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int64 | PubchemFP790
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1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4.37841 |
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𧬠Ubiquitin Carboxy-terminal L1 Hydrolase Target Bioactivity Dataset.
π Table of Contents
- β¨ Introduction
- π Dataset Overview
- π Features
- β¬οΈ Downloading the Dataset
- π‘ Example
- π€ Contributing
- π License
- π« Contact
β¨ Introduction
Welcome to the Ubiquitin L1 Hydrolase Target Bioactivity Dataset! This open-source dataset is meticulously curated to support machine learning applications in drug discovery and biochemical research focused on Ubiquitin L1 Hydrolase (Ubiquitin L1H). The dataset comprises compounds that have demonstrated activity or inactivity in the Ubiquitin L1 Hydrolase binding site, determined based on their ICβ β values. Whether you're developing predictive models or conducting exploratory analysis, this dataset provides high-quality data essential for understanding compound interactions with Ubiquitin L1 Hydrolase.
π Dataset Overview
- Total Samples: 17,421 compounds
- Active Compounds: 3,272
- Inactive Compounds: 14,149
- Categorization Criteria:
- Active: Compounds exhibiting significant binding activity with Ubiquitin L1 Hydrolase based on ICβ β β€ threshold_value ΞΌM.
- Inactive: Compounds showing no significant binding activity with ICβ β > threshold_value ΞΌM.
- Data Sources:
- PubChem
- ChEMBL
- Custom experimental data
- Features:
- SMILES: Simplified Molecular-Input Line-Entry System representation
- Molecular Descriptors: e.g., Molecular Weight, LogP, etc.
- Bioactivity Scores: ICβ β values
- Target Information: Binding affinity details
- Format: Available in CSV and JSON formats
π Features
- Rich Feature Set: Comprehensive molecular descriptors and bioactivity scores for in-depth analysis.
- High-Quality Annotations: Verified and standardized data ensuring reliability.
- Extensive Metadata: Includes references to original data sources and experimental conditions.
- ICβ β-Based Classification: Clear distinction between active and inactive compounds based on standardized ICβ β thresholds.
β¬οΈ Downloading the Dataset
You can download the dataset directly from Hugging Face or clone the repository to access the data files.
Direct Download Links
Download the dataset files in your preferred format:
- CSV Format:
- JSON Format:
Using Git LFS
If you prefer to clone the repository to access the dataset files, follow these steps:
Install Git LFS:
Git Large File Storage (LFS) is required to handle large dataset files.
# For macOS brew install git-lfs # For Windows choco install git-lfs # For Linux sudo apt-get install git-lfs
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