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The dataset generation failed because of a cast error
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 14 new columns ({'ICD10_ID', 'DO_ID', 'DO_Name', 'OMIM_ID', 'ICD11_Title', 'MeSH_Name', 'MONDO_ID', 'MeSH_ID', 'ICD11_ID', 'SNOMEDCT_ID', 'MONDO_Name', 'UMLS_Name', 'SNOMEDCT_Name', 'UMLS_ID'}) and 1 missing columns ({'Type'}).

This happened while the csv dataset builder was generating data using

hf://datasets/FuhaiLiAiLab/BioMedGraphica/BioMedGraphica-Conn/Entity/Disease/BioMedGraphica_Conn_Disease.csv (at revision caa5502cca807df484eab5f6bcb8aa71c8ce7b4f)

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 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, 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 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              BioMedGraphica_Conn_ID: string
              BioMedGraphica_ID: string
              SNOMEDCT_ID: string
              UMLS_Name: string
              MeSH_Name: string
              ICD11_ID: string
              ICD11_Title: string
              ICD10_ID: string
              DO_ID: string
              DO_Name: string
              UMLS_ID: string
              MeSH_ID: string
              OMIM_ID: string
              MONDO_ID: string
              MONDO_Name: string
              SNOMEDCT_Name: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2181
              to
              {'BioMedGraphica_Conn_ID': Value('string'), 'BioMedGraphica_ID': Value('string'), 'Type': Value('string')}
              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 1451, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 994, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, 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 1833, 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 14 new columns ({'ICD10_ID', 'DO_ID', 'DO_Name', 'OMIM_ID', 'ICD11_Title', 'MeSH_Name', 'MONDO_ID', 'MeSH_ID', 'ICD11_ID', 'SNOMEDCT_ID', 'MONDO_Name', 'UMLS_Name', 'SNOMEDCT_Name', 'UMLS_ID'}) and 1 missing columns ({'Type'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/FuhaiLiAiLab/BioMedGraphica/BioMedGraphica-Conn/Entity/Disease/BioMedGraphica_Conn_Disease.csv (at revision caa5502cca807df484eab5f6bcb8aa71c8ce7b4f)
              
              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.

BioMedGraphica_Conn_ID
string
BioMedGraphica_ID
string
Type
string
BMGC_PM00001
BMG_PM000001
Promoter
BMGC_PM00002
BMG_PM000002
Promoter
BMGC_PM00003
BMG_PM000003
Promoter
BMGC_PM00004
BMG_PM000004
Promoter
BMGC_PM00005
BMG_PM000005
Promoter
BMGC_PM00006
BMG_PM000006
Promoter
BMGC_PM00007
BMG_PM000007
Promoter
BMGC_PM00008
BMG_PM000017
Promoter
BMGC_PM00009
BMG_PM000018
Promoter
BMGC_PM00010
BMG_PM000019
Promoter
BMGC_PM00011
BMG_PM000020
Promoter
BMGC_PM00012
BMG_PM000022
Promoter
BMGC_PM00013
BMG_PM000023
Promoter
BMGC_PM00014
BMG_PM000024
Promoter
BMGC_PM00015
BMG_PM000025
Promoter
BMGC_PM00016
BMG_PM000027
Promoter
BMGC_PM00017
BMG_PM000030
Promoter
BMGC_PM00018
BMG_PM000038
Promoter
BMGC_PM00019
BMG_PM000040
Promoter
BMGC_PM00020
BMG_PM000041
Promoter
BMGC_PM00021
BMG_PM000042
Promoter
BMGC_PM00022
BMG_PM000043
Promoter
BMGC_PM00023
BMG_PM000044
Promoter
BMGC_PM00024
BMG_PM000045
Promoter
BMGC_PM00025
BMG_PM000046
Promoter
BMGC_PM00026
BMG_PM000047
Promoter
BMGC_PM00027
BMG_PM000048
Promoter
BMGC_PM00028
BMG_PM000049
Promoter
BMGC_PM00029
BMG_PM000050
Promoter
BMGC_PM00030
BMG_PM000051
Promoter
BMGC_PM00031
BMG_PM000052
Promoter
BMGC_PM00032
BMG_PM000053
Promoter
BMGC_PM00033
BMG_PM000054
Promoter
BMGC_PM00034
BMG_PM000055
Promoter
BMGC_PM00035
BMG_PM000056
Promoter
BMGC_PM00036
BMG_PM000057
Promoter
BMGC_PM00037
BMG_PM000058
Promoter
BMGC_PM00038
BMG_PM000059
Promoter
BMGC_PM00039
BMG_PM000060
Promoter
BMGC_PM00040
BMG_PM000061
Promoter
BMGC_PM00041
BMG_PM000062
Promoter
BMGC_PM00042
BMG_PM000063
Promoter
BMGC_PM00043
BMG_PM000064
Promoter
BMGC_PM00044
BMG_PM000065
Promoter
BMGC_PM00045
BMG_PM000066
Promoter
BMGC_PM00046
BMG_PM000067
Promoter
BMGC_PM00047
BMG_PM000068
Promoter
BMGC_PM00048
BMG_PM000069
Promoter
BMGC_PM00049
BMG_PM000070
Promoter
BMGC_PM00050
BMG_PM000071
Promoter
BMGC_PM00051
BMG_PM000072
Promoter
BMGC_PM00052
BMG_PM000073
Promoter
BMGC_PM00053
BMG_PM000074
Promoter
BMGC_PM00054
BMG_PM000075
Promoter
BMGC_PM00055
BMG_PM000076
Promoter
BMGC_PM00056
BMG_PM000077
Promoter
BMGC_PM00057
BMG_PM000078
Promoter
BMGC_PM00058
BMG_PM000079
Promoter
BMGC_PM00059
BMG_PM000080
Promoter
BMGC_PM00060
BMG_PM000081
Promoter
BMGC_PM00061
BMG_PM000082
Promoter
BMGC_PM00062
BMG_PM000083
Promoter
BMGC_PM00063
BMG_PM000084
Promoter
BMGC_PM00064
BMG_PM000085
Promoter
BMGC_PM00065
BMG_PM000086
Promoter
BMGC_PM00066
BMG_PM000087
Promoter
BMGC_PM00067
BMG_PM000088
Promoter
BMGC_PM00068
BMG_PM000089
Promoter
BMGC_PM00069
BMG_PM000090
Promoter
BMGC_PM00070
BMG_PM000091
Promoter
BMGC_PM00071
BMG_PM000092
Promoter
BMGC_PM00072
BMG_PM000093
Promoter
BMGC_PM00073
BMG_PM000094
Promoter
BMGC_PM00074
BMG_PM000095
Promoter
BMGC_PM00075
BMG_PM000096
Promoter
BMGC_PM00076
BMG_PM000097
Promoter
BMGC_PM00077
BMG_PM000098
Promoter
BMGC_PM00078
BMG_PM000099
Promoter
BMGC_PM00079
BMG_PM000100
Promoter
BMGC_PM00080
BMG_PM000101
Promoter
BMGC_PM00081
BMG_PM000102
Promoter
BMGC_PM00082
BMG_PM000103
Promoter
BMGC_PM00083
BMG_PM000104
Promoter
BMGC_PM00084
BMG_PM000105
Promoter
BMGC_PM00085
BMG_PM000106
Promoter
BMGC_PM00086
BMG_PM000107
Promoter
BMGC_PM00087
BMG_PM000108
Promoter
BMGC_PM00088
BMG_PM000109
Promoter
BMGC_PM00089
BMG_PM000110
Promoter
BMGC_PM00090
BMG_PM000111
Promoter
BMGC_PM00091
BMG_PM000112
Promoter
BMGC_PM00092
BMG_PM000113
Promoter
BMGC_PM00093
BMG_PM000114
Promoter
BMGC_PM00094
BMG_PM000115
Promoter
BMGC_PM00095
BMG_PM000116
Promoter
BMGC_PM00096
BMG_PM000117
Promoter
BMGC_PM00097
BMG_PM000118
Promoter
BMGC_PM00098
BMG_PM000119
Promoter
BMGC_PM00099
BMG_PM000120
Promoter
BMGC_PM00100
BMG_PM000121
Promoter
End of preview.

BioMedGraphica

BioMedGraphica is an all-in-one platform for biomedical data integration and knowledge graph generation. It harmonizes fragmented biomedical datasets into a unified, graph AI-ready resource that facilitates precision medicine, therapeutic target discovery, and integrative biomedical AI research.

Developed using data from 43 biomedical databases, BioMedGraphica integrates:

  • 11 entity types
  • 30 relation types
  • Over 2.3 million entities and 27 million relations

✨ Highlights

  • Multi-omics integration: Genomic, transcriptomic, proteomic, metabolomic, microbiomic, exposomic
  • Graph AI-ready: Outputs subgraphs ready for GNNs and ML models
  • Soft matching: Uses BioBERT for fuzzy entity resolution (disease, phenotype, drug, exposure)
  • GUI software: Provides Windows-based interface for end-to-end pipeline
  • Connected graph variant: Isolated nodes removed for efficient downstream training

πŸ“Š Dataset Statistics

Metric Count
Total Entities 2,306,921
Total Relations 27,232,091
Connected Entities 834,809
Connected Relations 27,087,971
Entity Types 11
Relation Types 30

🧬 Entity Types

Entity Type Count Percentage (%) Connected Count Connected (%)
Promoter 230,358 9.99 86,238 10.33
Gene 230,358 9.99 86,238 10.33
Transcript 412,326 17.87 412,039 49.36
Protein 173,978 7.54 121,419 14.54
Pathway 6,793 0.29 1,930 0.23
Metabolite 218,335 9.46 62,364 7.47
Microbiota 621,882 26.96 1,119 0.13
Exposure 1,159 0.05 1,037 0.12
Phenotype 19,532 0.85 19,078 2.29
Disease 118,814 5.15 22,429 2.69
Drug 273,386 11.85 20,918 2.51
Total 2,306,921 100 834,809 100

πŸ”— Relation Types

Relation Type Count Percentage (%)
Promoter-Gene 230,358 0.85
Gene-Transcript 427,810 1.57
Transcript-Protein 152,585 0.56
Protein-Protein 16,484,820 60.53
Protein-Pathway 152,912 0.56
Protein-Phenotype 478,279 1.76
Protein-Disease 143,394 0.53
Pathway-Protein 176,133 0.65
Pathway-Drug 1,795 0.01
Pathway-Exposure 301,448 1.11
Metabolite-Protein 2,804,430 10.30
Metabolite-Pathway 12,198 0.04
Metabolite-Metabolite 931 0.003
Metabolite-Disease 24,970 0.09
Microbiota-Disease 22,371 0.08
Microbiota-Drug 866 0.003
Exposure-Gene 28,982 0.11
Exposure-Pathway 301,448 1.11
Exposure-Disease 979,780 3.60
Phenotype-Phenotype 23,427 0.09
Phenotype-Disease 181,192 0.67
Disease-Phenotype 181,192 0.67
Disease-Disease 12,006 0.04
Drug-Protein 84,859 0.31
Drug-Pathway 3,065 0.01
Drug-Metabolite 3,589 0.01
Drug-Microbiota 866 0.003
Drug-Phenotype 93,826 0.34
Drug-Disease 39,977 0.15
Drug-Drug 3,882,582 14.26
Total 27,232,091 100

πŸ“¦ Access and Downloads

πŸ§ͺ Validation

  • Hard matching for structured identifiers (e.g. Ensembl, HGNC)
  • BioBERT-based soft matching for flexible terms (e.g., diseases, phenotypes, drugs)
  • Case study and benchmarking with Synapse dataset

πŸ“š Citation

@article{zhang2024biomedgraphica,
title={BioMedGraphica: An All-in-One Platform for Biomedical Prior Knowledge and Omic Signaling Graph Generation},
author={Zhang, Heming and Liang, Shunning and Xu, Tim and Li, Wenyu and Huang, Di and Dong, Yuhan and Li, Guangfu and Miller, J Philip and Goedegebuure, S Peter and Sardiello, Marco and others},
journal={bioRxiv},
year={2024}
}
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