A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

A variety of biological sequence classification task, such as species classification, gene function classification, and wire host classification are expected processes in many metagenomic data analyzes. Since metagenomic data contain a large number of Novo species and genes, high performing classification organisms are needed in many studies. Biologists often encounter challenge in finding suitable sequence classification and notation tools for a specific task and are often not able to construct a corresponding organism on their own because of a lack of the necessary mathematical and computational knowledge.

Deep learning techniques have recently become a popular topic and show strong advantage in many classification tasks. To date, many highly packaged deep learning package, which make it possible for biologists to construct deep learning frameworks, according to their own needs without in depth knowledge of the organism details have been developed. In this tutorial, we provide a guideline for constructing an easy to use deep learning framework for sequence classification without the need for sufficient mathematical knowledge or programming skills.