Webinar: Phylogenetic inference for pandemic-scale data

In the face of the global COVID-19 pandemic affecting all aspects of human life, the journal Nature has published leading experts in bioinformatics around the world calling on authorities to invest in solving computational challenges in phylogenetic tree reconstruction. Addressing these challenges will enable the development of monitoring systems on the evolution and spread of the SARS-CoV-2 virus so that communities are proactive if new virus strains arise. This report first presents the problem of tree reliability assessment, which plays a crucial role in helping these monitoring systems deliver the prediction with a proper confidence level. In addition, we present the problem of online tree reconstruction to add some query species (for example, a new sample collected during this outbreak) on an existing tree (e.g., tree of the previous outbreak) arising from the very context of using pandemic data. With both problems, we are conducting research to analyze pandemic-scale data because this is an urgent need for biodiversity research (applied not only in virus evolution study but also in drug design, vaccines, agriculture, and climate change response).