Datasets:

Xiaowei0402
/

uniprot_subcellular_localization

pretty_name: UniProt Subcellular Localization (Vertebrates) — ProVADA
tags:
  - biology
  - proteins
  - uniprot
  - subcellular-localization
  - classification
size_categories:
  - 10K<n<100K
license: cc-by-4.0

UniProt Subcellular Localization (Vertebrates) — ProVADA

A curated collection of vertebrate UniProt/Swiss‑Prot protein domains labeled for cytosolic and extracellular localization. We remove signal peptides, restrict domain lengths, and provide both the full set and a 30% identity‑clustered representative set with train/test/validation splits (70/20/10). This dataset underpins the subcellular localization oracle in ProVADA (preprint).

Dataset Description

Source: UniProt Swiss‑Prot, vertebrate entries with experimental evidence for subcellular localization.
Scope: Cytosolic and extracellular proteins and domains (including secreted proteins and extracellular regions of transmembrane proteins), signal sequences excluded.
Granularity: Mature protein domains within 50–1000 aa.
Balanced representation: MMseqs2 clustering at 30% sequence similarity threshold, keeping one representative per cluster, to ensure balanced representation of protein families.
Splits: Stratified train/test/val = 70%/20%/10% on the representative set.
Total size (full set): 10,652 domains (4,635 cytosolic only; 5,917 extracellular only; 100 with both labels).

See the Files section for exact filenames and formats.

Supported Tasks

Sequence classification: Predicting whether a protein domain is viable in the cytosol/extracellular space.
Protein representation learning: Pretraining or evaluating embeddings for subcellular localization viability.

Languages / Alphabets

Amino‑acid sequences using the standard 20‑letter alphabet (uppercase single‑letter codes).

Data Structure

Files

full_dataset.csv — Full curated set (10,652 domains).
representative_data_train.csv, representative_data_val.csv, representative_data_test.csv — 30%‑identity clustered representative set with predefined splits for model development.

Column schema is consistent across files.

Fields

sequence (str) — Amino‑acid sequence of the domain.
converted_id (str) — UniProt accession plus the domain region in brackets (e.g., P12345[35-210]).
cytosolic_label (bool) — True if the domain localizes to the intracellular/cytosolic region.
extracellular_label (bool) — True if the domain localizes to the extracellular space (secreted or extracellular domain of a TM protein).

Notes:

The two labels are not mutually exclusive; a small number of domains have both annotations.
For TM proteins we include only the annotated extracellular domain within the length range.

Processing & Quality Control

Curation from Swiss‑Prot. We include entries with experimental evidence and exclude organelles such as lysosomes, endosomes, peroxisomes, and mitochondria.
Domain extraction. We keep mature regions only (signal sequences removed). Where multiple domains are annotated, we retain shorter, individual domains between 50–1000 aa. For transmembrane proteins, we extract annotated extracellular domains within this length.
Redundancy control. We cluster all sequences using MMseqs2 at 30% identity and keep one representative/cluster.
Splitting. We create stratified train/test/validation splits on the representative subset to balance labels and protein families.

Suggested evaluation splits

If you only need a single‑split for quick evaluation, prefer the representative set (representative_data_*.csv) to reduce family‑level redundancy.

Licensing

Upstream data: Derived from UniProt/Swiss‑Prot (released under CC BY 4.0).
This dataset release: CC BY 4.0. Please ensure your downstream use complies with UniProt’s terms and institutional policies.

Citation

If you use this dataset, please cite the ProVADA preprint where the curation procedure and usage are described:

@article{Lu2025,
  title = {ProVADA: Generation of Subcellular Protein Variants via Ensemble-Guided Test-Time Steering},
  url = {http://dx.doi.org/10.1101/2025.07.11.664238},
  DOI = {10.1101/2025.07.11.664238},
  publisher = {Cold Spring Harbor Laboratory},
  author = {Lu, Wenhui Sophia and Zhang, Xiaowei and Mille-Fragoso, Luis S. and Dai, Haoyu and Gao, Xiaojing J. and Wong, Wing Hung},
  year = {2025},
  month = jul
}