The initiate site of DNA replication is called origins of replication (ORI) which is regulated by a set of regulatory proteins and plays important roles in the basic biochemical process during cell growth and division in all living organisms. Therefore, the study of ORIs is essential for understanding the cell-division cycle and gene expression regulation so that scholars can develop a new strategy against genetic diseases by using the knowledge of DNA replication. Thus, the accurate identification of ORIs will provide key clues for DNA replication research and clinical medicine. Although, the conventional experiments could provide accurate results, they are time-consuming and cost ineffective. On the contrary, bioinformatics-based methods can overcome these shortcomings. Especially, with the emergence of DNA sequences in the post-genomic era, it is highly expected to develop high throughput tools to identify ORIs based on sequence information. In this review, we will summarize the current progress in computational prediction of eukaryotic ORIs including the collection of benchmark dataset, the application of machine learning-based techniques, the results obtained by these methods, and the construction of web servers. Finally, we gave the future perspectives on ORIs prediction. The review provided readers with a whole background of ORIs prediction based on machine learning methods, which will be helpful for researchers to study DNA replication in-depth and drug therapy of genetic defect.
Keywords: DNA structure properties; eukaryotic DNA replication; machine learning method; origins of replication; webserver.