Datasets:
| 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 | |