CIBB, University of Coimbra, Coimbra, Portugal; IIIs-Institute for Interdisciplinary Research, University of Coimbra, Coimbra, Portugal.
CIBB, University of Coimbra, Coimbra, Portugal; Department of Sciences, University of Porto, Porto, Portugal; CNC-Center for Neuroscience and Cell Biology, CIBB-Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.
Methods Cell Biol. 2022;169:169-198. doi: 10.1016/bs.mcb.2022.02.001. Epub 2022 Mar 4.
Viruses are a diverse biological group capable of infecting several hosts such as bacteria, plants, and animals, including humans. Viral infections constitute a threat to the human population as they may cause high mortality rates, decrease food production, and generate large economical losses. Viruses co-evolve with their hosts and this constant evolution must be clarified to better predict possible viral outbreaks, and to develop improved diagnostic methods and therapeutical approaches. In this review, we summarize several viral databases that store key information retrieved from a variety of omics approaches. Furthermore, we explore the use of such databases to predict Virus-Host interactions through artificial intelligence algorithms, focusing on the latest methodologies to characterize biological networks.
病毒是一种多样化的生物群体，能够感染包括人类在内的多种宿主，如细菌、植物和动物。病毒感染对人类构成威胁，因为它们可能导致高死亡率、减少粮食产量和造成巨大的经济损失。病毒与其宿主共同进化，必须澄清这种不断的进化，以更好地预测可能的病毒爆发，并开发改进的诊断方法和治疗方法。在这篇综述中，我们总结了几个存储从各种组学方法中提取的关键信息的病毒数据库。此外，我们还探讨了通过人工智能算法利用这些数据库来预测病毒-宿主相互作用，重点介绍了最新的生物网络特征化方法。
