Datasets:
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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`.
|