---
license: mit
task_categories:
  - token-classification
language:
  - en
tags:
  - protein
  - bioinformatics
  - secondary-structure
  - deep-learning
size_categories:
  - 1K<n<10K
---

# Protein Secondary Structure Prediction Dataset (NPPE2)

## Dataset Description

This dataset contains protein sequences with their corresponding secondary structure labels for both Q8 (8-class) and Q3 (3-class) classification tasks.

### Dataset Statistics

| Split | Sequences |
|-------|-----------|
| Train | 7262 |
| Test  | 1816 |

### Features

- **id**: Unique identifier for each protein sequence
- **seq**: Amino acid sequence (20 standard amino acids)
- **sst8**: 8-class secondary structure labels (Q8)
- **sst3**: 3-class secondary structure labels (Q3)

### Secondary Structure Labels

**Q8 Labels (DSSP):**
- H = Alpha helix
- E = Beta strand
- C = Coil/Loop
- G = 3-10 helix
- B = Beta bridge
- T = Turn
- S = Bend
- I = Pi helix

**Q3 Labels:**
- H = Helix (H, G, I)
- E = Strand (E, B)
- C = Coil (C, T, S)

### Usage

`python
from datasets import load_dataset

dataset = load_dataset("neuralninja110/dlgenai-nppe-dataset")
`

### Files

- train.csv: Training data with sequences and labels
- test.csv: Test data (sequences only)
- sample_submission.csv: Submission format template
- data/train.parquet: Training data in parquet format

### Evaluation Metric

Harmonic mean of F1 scores for Q8 and Q3 predictions.

### License

MIT License