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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- en |
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tags: |
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- biology |
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- chemistry |
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- medical |
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pretty_name: ProteinFamilyClassification |
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size_categories: |
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- 1K<n<10K |
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--- |
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## Dataset Description |
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This dataset contains a curated subset (14% of the original) of protein sequences from the **Astral SCOPe 2.08 genetic domain sequence subsets**. |
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It is designed for **protein family classification** tasks, where the goal is to assign each amino acid sequence to its corresponding **SCOPe family**. |
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### Key Features |
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- **Source:** Derived from the SCOPe database, which provides a hierarchical classification of protein structural domains based on experimental structural data from the Protein Data Bank (PDB). |
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- **Classes:** Seven SCOPe protein classes (a–g), covering alpha proteins, beta proteins, mixed alpha/beta proteins, multi-domain proteins, membrane proteins, and small proteins. |
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- **Embeddings:** Precomputed embeddings generated using the **ESM-2 transformer model** from Meta AI, allowing researchers to skip the computationally expensive embedding step. |
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- **Purpose:** Ideal for training and testing classification models on protein sequence data with minimal preprocessing. |
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### Why This Dataset? |
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Generating embeddings for the full dataset takes ~3-7 hours on typical hardware. This preprocessed version provides a ready-to-use format for quick experimentation, making it accessible to teams with limited compute resources. |
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### Potential Uses |
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- Benchmarking machine learning models for protein classification. |
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- Experimenting with XGBoost, MLP, CNN, or other classifiers. |
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- Teaching and demonstration purposes in bioinformatics and computational biology. |
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--- |
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