Survey of deep learning techniques for disease prediction based on omics data

In the era of big data, computer science has been applied to every aspect of biomedical field. At the same time, transforming biomedical data into valuable knowledge is one of the most important challenges of bioinformatics. Consequently, the birth of deep learning algorithms has greatly promoted the development of bioinformatics as a result of its ability to incorporate existing knowledge from vast datasets. In this review, we focus on the related deep learning techniques based on omics in the direction of disease prediction and present brief descriptions and comments of these studies based on DNA, RNA, protein and multi-omics datasets. Finally, we give the statistical results of the types and numbers of papers published in the field of disease prediction and discuss the potential development of deep learning in this field.