---
annotations_creators:
 - no-annotation
language_creators:
 - found
language:
 - en
license:
 - other
multilinguality:
 - monolingual
size_categories:
 - 1K1T
source_datasets:
 - original
task_categories:
 - text-generation
 - question-answering
task_ids: []
paperswithcode_id:
pretty_name: NN / PeptideBench / synthetic_peptides
tags:
 - peptide-bench
 - synthetic_peptides
---
# Dataset **synthetic_peptides**

## Description
 Synthetic peptide sequences using p2smi generate_sequences function
```
{
  "loading_mode": "test",
  "max_num": null,
  "shuffled": false,
  "seed": 42,
  "name": "synthetic_peptides",
  "description": "Synthetic peptide sequences using p2smi generate_sequences function",
  "data_dir": "/var/folders/1d/6n6fqgcj30j83xsfxydcjsxw0000gq/T/tmplwzp68ft",
  "augmentations": [
    "p2smi",
    "isoelectric_point",
    "LIN2CYC",
    "cyclic_ring_size",
    "CYC"
  ],
  "remove_na_rows": true,
  "train_generation_config": {
    "id_prefix": "synth_peptide_train",
    "num_peptides": 800,
    "min_length": 5,
    "max_length": 11,
    "noncanonical_percent": 0.1,
    "dextro_percent": 0.2,
    "constraints": []
  },
  "test_generation_config": {
    "id_prefix": "synth_peptide_test",
    "num_peptides": 200,
    "min_length": 5,
    "max_length": 11,
    "noncanonical_percent": 0.1,
    "dextro_percent": 0.2,
    "constraints": []
  }
}
```
## Dataset splits

### **train**: 800 examples
```
{'uid': Value(dtype='string', id=None), 'id': Value(dtype='string', id=None), 'sequence': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'linear_peptide_smiles': Value(dtype='string', id=None), 'standardized_smiles': Value(dtype='string', id=None), 'expected_isoelectric_point': Value(dtype='float64', id=None), 'expected_cyclic_smiles': Value(dtype='string', id=None), 'expected_ring_size': Value(dtype='int64', id=None), 'smiles': Value(dtype='string', id=None), 'expected_cyclicity': Value(dtype='string', id=None)}
```
- Preprocessing statistics

```
{
  "p2smi": {
    "success": 800,
    "fail": 0
  },
  "isoelectric_point": {
    "success": 800,
    "fail": 0
  },
  "LIN2CYC": {
    "success": 800,
    "fail": 0
  },
  "cyclic_ring_size": {
    "success": 800,
    "fail": 0
  },
  "CYC": {
    "success": 800,
    "fail": 0
  }
}
```
### **test**: 200 examples
```
{'uid': Value(dtype='string', id=None), 'id': Value(dtype='string', id=None), 'sequence': Value(dtype='string', id=None), 'description': Value(dtype='string', id=None), 'linear_peptide_smiles': Value(dtype='string', id=None), 'standardized_smiles': Value(dtype='string', id=None), 'expected_isoelectric_point': Value(dtype='float64', id=None), 'expected_cyclic_smiles': Value(dtype='string', id=None), 'expected_ring_size': Value(dtype='int64', id=None), 'smiles': Value(dtype='string', id=None), 'expected_cyclicity': Value(dtype='string', id=None)}
```
- Preprocessing statistics

```
{
  "p2smi": {
    "success": 200,
    "fail": 0
  },
  "isoelectric_point": {
    "success": 200,
    "fail": 0
  },
  "LIN2CYC": {
    "success": 200,
    "fail": 0
  },
  "cyclic_ring_size": {
    "success": 200,
    "fail": 0
  },
  "CYC": {
    "success": 200,
    "fail": 0
  }
}
```


Uploaded at 2025-11-25 08:20:51.771563