Phylogenies as graphs: structured neural networks improve host origin predictions from paramyxovirus sequences
Accurately identifying the host of a virus from its genome sequence is a task with important applications in zoonotic disease surveillance and filling data gaps for metagenomic sampling. Machine learning approaches have seen broad application in making host predictions directly from viral genome sequences. However, most host prediction models do not incorporate information on viral phylogeny,…
We haven't written up this one. bioRxiv has the full story — the link below goes straight to it.
