TY - JOUR AU - Lu, Congyu AU - Zhang, Zheng AU - Cai, Zena AU - Zhu, Zhaozhong AU - Qiu, Ye AU - Wu, Aiping AU - Jiang, Taijiao AU - Zheng, Heping AU - Peng, Yousong PY - 2021 DA - 2021/01/14 TI - Prokaryotic virus host predictor: a Gaussian model for host prediction of prokaryotic viruses in metagenomics JO - BMC Biology SP - 5 VL - 19 IS - 1 AB - Viruses are ubiquitous biological entities, estimated to be the largest reservoirs of unexplored genetic diversity on Earth. Full functional characterization and annotation of newly discovered viruses requires tools to enable taxonomic assignment, the range of hosts, and biological properties of the virus. Here we focus on prokaryotic viruses, which include phages and archaeal viruses, and for which identifying the viral host is an essential step in characterizing the virus, as the virus relies on the host for survival. Currently, the method for determining the viral host is either to culture the virus, which is low-throughput, time-consuming, and expensive, or to computationally predict the viral hosts, which needs improvements at both accuracy and usability. Here we develop a Gaussian model to predict hosts for prokaryotic viruses with better performances than previous computational methods. SN - 1741-7007 UR - https://doi.org/10.1186/s12915-020-00938-6 DO - 10.1186/s12915-020-00938-6 ID - Lu2021 ER -