Editorial: Artificial Intelligence Bioinformatics: Development and Application of Tools for Omics and Inter-Omics Studies
For half a century, bioinformatics and computational biology have provided tools and data analysis approaches, so the beginning of the omics era represented a novel challenge for researchers, that converged to the area of bioinformatics from the fields of informatics, mathematics, and statistics. In most cases, the solutions offered appeared difficult to use for researchers working in biomedical areas. This occurred in particular when sophisticated approaches from the field of data science and artificial intelligence (AI), were applied to biomedical data (Lisboa et al., 2000). Machine learning, statistical learning, and soft-computing approaches, such as deep neural networks or genetic algorithms, have also become terms used in the bio world, with an incomplete comprehension however, of their potential (Pavel et al., 2016; Lin and Lane, 2017; Zeng and Lumley, 2018). In recent years, omics, multi-omics, and inter-omics experiments have presented a further step toward the investigation in biology, opening the window on personalized medicine, for example for diagnostics (Riemenschneider et al., 2016). The era of big data in medicine is imminent and represents yet a further step forward. Considering this, our Research Topic presents articles on novel developments in the field of artificial intelligence in biology and medicine, and their applications in the analysis of high-throughput data from omics and inter-omics approaches (Facchiano et al.).