geometric-intelligence/ogbench
OgBench: Benchmarking Graph Neural Networks on Omics Data OgBench is the first benchmark suite for graph-level prediction in the n ≪ p regime characteristic of omics data, where the number of patient samples n is much smaller than the number of nodes (genes or proteins) p per graph. Datasets This repository contains four preprocessed omics graph classification datasets: Dataset Modality n p Task HERITAGE Proteomics 654 4,977 Exercise responder… See the full description on the dataset page: https://huggingface.co/datasets/geometric-intelligence/ogbench.
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1{2 "dataset_name": "tuberculosis",3 "download_urls": {4 "GSE19433": "https://ftp.ncbi.nlm.nih.gov/geo/series/GSE19nnn/GSE19433/matrix/GSE19433_series_matrix.txt.gz",5 "GPL9790_platform": "https://ftp.ncbi.nlm.nih.gov/geo/platforms/GPL9nnn/GPL9790/soft/GPL9790_family.soft.gz",6 "UniProt_H37Rv_proteome": "https://rest.uniprot.org/uniprotkb/stream?query=proteome:UP000001584&fields=accession,reviewed,gene_oln&format=tsv"7 },8 "download_timestamp": "2026-06-30T11:57:18.314708",9 "statistics": {10 "num_samples": 561,11 "num_features": 3814,12 "target_stats": {13 "class_mapping": {14 "NEG": 0,15 "POS": 116 },17 "num_classes": 2,18 "class_names": [19 "NEG",20 "POS"21 ],22 "samples_per_class": {23 "NEG": 307,24 "POS": 25425 }26 }27 },28 "preprocessing_notes": "GSE19433 M. tuberculosis full-proteome antibody microarray (platform GPL9790, log-transformed raw intensities without normalization). The classification target is the M. tuberculosis culture result (0=NEG, 1=POS); samples with culture \"not applicable\" are dropped. Microarray spot ids (block_row_column) are mapped to M. tuberculosis ORFs (Rv locus tags) via the GPL9790 platform table; array-specific segment/alt spots (\"-s1\", \"-alt\") are collapsed to the base locus tag by averaging. Rv locus tags are mapped to UniProt accessions via the H37Rv reference proteome (UP000001584); spots that do not resolve to a UniProt accession are discarded."29}