--- pretty_name: InterPro Entries license: other tags: - biology - protein - protein-family - protein-domain - interpro - ontology - parquet configs: - config_name: default data_files: - split: train path: data/train-*.parquet - split: test path: data/test-*.parquet --- # InterPro Entries This dataset contains a viewer-friendly Parquet table derived from the InterPro current release files in this repository. Each row is one InterPro entry from `current_release/interpro.xml.gz`. The original source release files remain in the repository. The default `datasets` configuration uses the normalized Parquet files under `data/` so that the Hugging Face Dataset Viewer and `load_dataset()` can read the entries directly. Large release artifacts such as `current_release/match_complete.xml.gz`, `current_release/protein2ipr.dat.gz`, and `current_release/sites.xml.gz` are preserved as source files but are not loaded by the default table. ## Splits The split is deterministic by InterPro identifier: `sha256(interpro_id) % 10`. Bucket `0` is `test`; buckets `1` through `9` are `train`. | Split | Rows | |---|---:| | train | 46,440 | | test | 5,049 | | total | 51,489 | ## Dataset Statistics | Field | Value | |---|---:| | InterPro release | `108.0` | | Release date | `29th January 2026` | | Entries | 51,489 | | Member database rows | 18 | | Entries with GO mappings | 14,799 | | InterPro-to-GO mapping rows | 30,200 | | Entries with structures | 30,172 | | Entries with publications | 38,194 | | Entry type | Rows | |---|---:| | Family | 27,308 | | Domain | 19,276 | | Homologous_superfamily | 3,510 | | Conserved_site | 768 | | Repeat | 395 | | Active_site | 133 | | Binding_site | 82 | | PTM | 17 | | GO category | Mappings | |---|---:| | molecular_function | 13,802 | | biological_process | 11,059 | | cellular_component | 5,339 | ## Usage Install the Hugging Face Datasets library: ```bash pip install datasets ``` Load all splits: ```python from datasets import load_dataset ds = load_dataset("LiteFold/InterPro") print(ds) row = ds["train"][0] print(row["interpro_id"], row["name"], row["entry_type"]) ``` Load one split: ```python from datasets import load_dataset train = load_dataset("LiteFold/InterPro", split="train") test = load_dataset("LiteFold/InterPro", split="test") ``` Stream rows without downloading the full table first: ```python from datasets import load_dataset stream = load_dataset("LiteFold/InterPro", split="train", streaming=True) for row in stream.take(5): print(row["interpro_id"], row["short_name"], row["protein_count"]) ``` Filter entries with GO mappings: ```python from datasets import load_dataset ds = load_dataset("LiteFold/InterPro", split="train") with_go = ds.filter(lambda row: row["go_count"] > 0) print(with_go[0]["interpro_id"], with_go[0]["go_ids"]) ``` Filter protein domains with PDB structures: ```python from datasets import load_dataset ds = load_dataset("LiteFold/InterPro", split="train") domains_with_structures = ds.filter( lambda row: row["entry_type"] == "Domain" and row["structure_count"] > 0 ) print(domains_with_structures[0]["interpro_id"], domains_with_structures[0]["pdb_ids"][:5]) ``` Load release database metadata directly: ```python import pandas as pd from huggingface_hub import hf_hub_download path = hf_hub_download( repo_id="LiteFold/InterPro", repo_type="dataset", filename="metadata/database_info.parquet", ) database_info = pd.read_parquet(path) print(database_info) ``` ## Columns | Column | Description | |---|---| | `interpro_id` | InterPro accession, such as `IPR000001`. | | `interpro_numeric_id` | Numeric portion of `interpro_id`. | | `name` | Full InterPro entry name. | | `short_name` | Short InterPro entry name from the XML attribute. | | `entry_type` | Entry class, such as `Family`, `Domain`, or `Homologous_superfamily`. | | `protein_count` | Number of proteins matched by the entry in the release XML. | | `is_llm` | Whether the entry is marked as LLM-generated in the source XML. | | `is_llm_reviewed` | Whether the LLM marker is reviewed in the source XML. | | `abstract` | Normalized text from the entry abstract. | | `go_ids` | GO identifiers mapped to the InterPro entry. | | `go_terms` | GO term names corresponding to `go_ids`. | | `go_categories` | GO namespaces corresponding to `go_ids`. | | `go_count` | Number of mapped GO terms. | | `member_databases` | Member databases contributing signatures. | | `member_accessions` | Signature accessions from member databases. | | `member_names` | Signature names from member databases. | | `member_protein_counts` | Protein counts for member signatures. | | `member_count` | Number of member signatures. | | `external_databases` | External resource database names. | | `external_accessions` | External resource accessions. | | `external_xrefs` | Combined external cross-references as `DB:ACCESSION`. | | `external_xref_count` | Number of external cross-references. | | `pdb_ids` | PDB structure identifiers. | | `structure_count` | Number of PDB structure links. | | `publication_ids` | InterPro publication identifiers. | | `pubmed_ids` | PubMed identifiers, when available. | | `publication_titles` | Publication titles. | | `publication_years` | Publication years, with `0` used when missing. | | `publication_count` | Number of publications attached to the entry. | | `parent_ids` | Parent InterPro entries from the XML hierarchy. | | `child_ids` | Child InterPro entries from the XML hierarchy. | | `parent_count` | Number of parents. | | `child_count` | Number of children. | | `tree_depth` | Minimum hierarchy depth from `ParentChildTreeFile.txt`, when present. | | `taxonomy_names` | Taxa listed in the taxonomy distribution. | | `taxonomy_protein_counts` | Protein counts for `taxonomy_names`. | | `taxonomy_count` | Number of taxonomy distribution rows. | | `key_species_names` | Key species names listed for the entry. | | `key_species_protein_counts` | Protein counts for `key_species_names`. | | `key_species_count` | Number of key species rows. | | `in_entry_list` | Whether the entry appears in `entry.list`. | | `entry_list_type` | Entry type from `entry.list`. | | `entry_list_name` | Entry name from `entry.list`. | | `names_dat_name` | Entry name from `names.dat`. | | `short_names_dat_name` | Short name from `short_names.dat`. | | `split_bucket` | Deterministic split bucket from `sha256(interpro_id) % 10`. | ## Preparation The normalization script used to create the Parquet files is included at `scripts/prepare_interpro_dataset.py`.