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+ ---
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+ license: mit
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+ tags:
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+ - genomics
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+ - bioinformatics
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+ - benchmark
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+ - grading
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+ - synonyms
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+ - databases
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+ - ncbi-gene
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+ - ncbi-taxonomy
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+ - mirbase
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+ - hmdb
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+ - card
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+ pretty_name: GenomicsBench Grader Databases
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+ size_categories:
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+ - 100M<n<1B
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+ ---
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+
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+ # GenomicsBench Grader Databases
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+
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+ Synonym databases for deterministic grading in [GenomicsBench](https://github.com/AfterQuery/GenomicsBench), a realism-first benchmark for AI coding agents in computational biology.
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+
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+ GenomicsBench ships with hundreds of prebuilt graders for highly specific biological outputs. These databases power the synonym-aware matching behind those graders, so that *TP53* and *tumor protein p53* are recognized as the same gene, *hsa-miR-21-5p* and *MIMAT0000076* as the same miRNA, and *E. coli* and *Escherichia coli* as the same organism.
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+
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+ ## Contents
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+
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+ Five tab-separated files, one per biological database. Each is a flat lookup table mapping canonical identifiers to all known names and synonyms.
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+
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+ | File | Columns | Rows | Source | Description |
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+ |---|---|---|---|---|
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+ | `ncbi_gene_grader_db.tsv` | `organism gene_id name` | 218M | [NCBI Gene](https://www.ncbi.nlm.nih.gov/gene/) | Gene symbol, synonym, description, Entrez GeneID, and Ensembl ID resolution scoped by organism |
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+ | `ncbi_taxonomy_grader_db.tsv` | `canonical_name name` | 3.2M | [NCBI Taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy) | Scientific name, common name, abbreviation, and synonym resolution for all taxa |
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+ | `hmdb_grader_db.tsv` | `accession name` | 2.0M | [HMDB](https://hmdb.ca/) | Metabolite name, synonym, IUPAC name, and accession resolution |
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+ | `mirbase_grader_db.tsv` | `accession name` | 185K | [miRBase](https://mirbase.org/) | miRNA precursor and mature name/accession resolution, including deprecated entries |
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+ | `card_grader_db.tsv` | `aro_accession name` | 19K | [CARD](https://card.mcmaster.ca/) | Antimicrobial resistance gene name, synonym, and ARO accession resolution |
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+
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+ For information on the provenance, licensing, or the ETL process generating this dataset, you should visit the [GenomicsBench GitHub repository](https://github.com/AfterQuery/GenomicsBench).