Randy Joy Magno Ventayen

Benchmarking CNN and LSTM Models for Genetic Mutation Classification across Diverse Sequence Encoding Techniques

This study evaluates four encoding schemes—one-hot, k-mer (substring-based encoding), embeddings, and Position-Specific Scoring Matrix (PSSM) using Convolutional Neural Networks (CNNs) and Long Short-Term Memories (LSTMs) and shows that k-mer encoding achieved the highest accuracy.