Ten computational challenges in human virome studies

Abstract

In recent years, substantial advancements have been achieved in understanding the diversity of the human virome and its intricate roles in human health and diseases. Despite this progress, the field of human virome research remains nascent, primarily hindered by the lack of effective methods, particularly in the domain of computational tools. This perspective systematically outlines ten computational challenges spanning various types of virome studies. These challenges arise due to the vast diversity of viromes, the absence of a universal marker gene in viral genomes, the low abundance of virus populations, the remote or minimal homology of viral proteins to known proteins, and the highly dynamic and heterogeneous nature of viromes. For each computational challenge, we discuss the underlying reasons, current research progress, and potential solutions. The resolution of these challenges necessitates ongoing collaboration among computational scientists, virologists, and multidisciplinary experts. In essence, this perspective serves as a comprehensive guide for directing computational efforts in human virome studies.

Keywords: Artificial intelligence; Computational biology; Computational viromics; Human virome.

Fig. 1

Ten computational challenges in human virome studies. Please see brief introductions to these challenges in the texts.