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{ "A": 5815579, "C": 1500850, "D": 3343400, "E": 4185569, "F": 3474724, "G": 4845379, "H": 1785930, "I": 4800530, "K": 4652096, "L": 7532011, "M": 3155363, "N": 3084064, "P": 3468676, "Q": 2706277, "R": 4917311, "S": 5404899, "T": 4066856, "V": 4879442, "W": 1054910, "Y": 2249592...
{ "accepted": 1937384, "noncanonical": 13009, "records_read": 1950393, "residue_count": 76923458 }
2026-09-26T12:49:44.792936+00:00
uniref50
Canonical UniRef50 representatives of length 1-50 for peptide MLM pretraining
{ "allowed_amino_acids": "ACDEFGHIKLMNPQRSTVWY", "deduplicate": false, "max_length": 50, "min_length": 1 }
{ "11": 4800, "12": 5486, "13": 5506, "14": 6076, "15": 6917, "16": 7489, "17": 8108, "18": 8585, "19": 9844, "20": 11957, "21": 13037, "22": 14646, "23": 15627, "24": 16756, "25": 17833, "26": 18850, "27": 20405, "28": 20503, "29": 37126, "30": 42501, "31": 44222, "32": 4498...
78,860,842
uniref50.txt
6da9fdbd1519eb9fb8ec61974817552f49f05ce279c0cb7aefc9a3f51a0958f0
/home/dataset-local/jiahui/pepbenchmark/PepBenchmark/datasets2/uniport/uniref_length_TO_50_AND_identity_0_5_2025_08_28.fasta
97dc59fb037ad50a37b3871d3219c53412510f661e5cd76d3865cff5c64ad416

PepBenchmark UniRef50 peptide pretraining corpus

This dataset contains UniRef50 representative sequences prepared for masked language-model continued pretraining in PepBenchmark. Each line of uniref50.txt is one upper-case amino-acid sequence. The file has no header.

Important version note

This is a reproducible reconstruction from the locally archived UniRef50 FASTA snapshot downloaded on 2025-08-28. It is suitable for new training runs, but it is not byte-identical to the unavailable historical corpus used by the original experiment.

Corpus Sequences Residues Length range
This reconstructed release 1,937,384 76,923,458 11-50
Historical experiment 1,932,360 76,692,615 11-50

Results from a new run should therefore be described as using the reconstructed 2025-08-28 corpus, rather than as an exact reproduction of the historical run.

Construction

The archived source contains 1,950,393 UniRef50 FASTA records. Construction:

  1. concatenate multiline FASTA sequence records;
  2. remove whitespace and normalize sequences to upper case;
  3. retain lengths from 1 through 50 amino acids (inclusive);
  4. retain only the 20 canonical amino acids ACDEFGHIKLMNPQRSTVWY;
  5. preserve source order and write one sequence per line without a header.

The source already contains only lengths 11-50. Canonical filtering removes 13,009 records and retains 1,937,384. No additional deduplication is applied; the retained sequences were audited and are unique.

Provenance and complete length/amino-acid counts are recorded in uniref50.metadata.json.

Integrity

uniref50.txt
size: 78,860,842 bytes
sha256: 6da9fdbd1519eb9fb8ec61974817552f49f05ce279c0cb7aefc9a3f51a0958f0

The archived source FASTA has SHA-256:

97dc59fb037ad50a37b3871d3219c53412510f661e5cd76d3865cff5c64ad416

Training preparation

From the peptide-esm repository root:

python preprocessing.py \
  --input_file ./pretrain_data/uniref50.txt \
  --output_dir ./processed_data/uniref50 \
  --validation_split 0.1 \
  --seed 42 \
  --min_length 1 \
  --max_length 50

This creates a deterministic split of 1,743,645 training sequences and 193,739 validation sequences. The model configuration can then read processed_data/uniref50/train.txt and processed_data/uniref50/validation.txt.

License and attribution

The underlying UniRef data are provided by the UniProt Consortium under CC BY 4.0. Users should cite UniProt/UniRef as appropriate. The reconstruction metadata does not replace the upstream database citation.

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