DNA Sequences Classification with Deep Learning: A Survey

Abstract

Deep learning (DL) methods have beenachieving amazing results in solving a variety ofproblems in many different fields especially in the areaof big data. With the advances of the big data era inbioinformatics, applying DL techniques, the DNAsequences can be classified with accurate and scalableprediction. The strength of DL methods come from thedevelopment of software and hardware, such asprocessing abilities graphical processing units (GPU) forthe hardware and new learning or inference algorithmsfor the software, which reducing the main primarydifficulties that faced the training process. In This work,we start from the previous classification methods such asalignment methods pointing out the problems, which areface to use these methods.After that, we demonstratedeep learning, from artificial neural networks to hyperparameter tuning, and the most recent state-of-the-artDL architectures used in DNA classification. After that,the paper ended with limitations and suggestions.