Dataset Description

This dataset contains a curated subset (14% of the original) of protein sequences from the Astral SCOPe 2.08 genetic domain sequence subsets.
It is designed for protein family classification tasks, where the goal is to assign each amino acid sequence to its corresponding SCOPe family.

Key Features

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).
Classes: Seven SCOPe protein classes (a–g), covering alpha proteins, beta proteins, mixed alpha/beta proteins, multi-domain proteins, membrane proteins, and small proteins.
Embeddings: Precomputed embeddings generated using the ESM-2 transformer model from Meta AI, allowing researchers to skip the computationally expensive embedding step.
Purpose: Ideal for training and testing classification models on protein sequence data with minimal preprocessing.

Why This Dataset?

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.

Potential Uses

Benchmarking machine learning models for protein classification.
Experimenting with XGBoost, MLP, CNN, or other classifiers.
Teaching and demonstration purposes in bioinformatics and computational biology.