A deep learning approach to DNA sequence classification: first results

Deep learning neural networks are capable to extract significant features from raw data, and to use these features for classification tasks. In this work we present a deep learning neural network for DNA sequence classification based on spectral sequence representation. The framework is tested on a dataset of 3000 16S genes and compared to the GRNN that we tested outperform the Support Vector Machine classification algorithm.