
pmid: 30385576
pmc: PMC6536379
Predicting hosts and vectorsDuring outbreaks of mysterious infections, events can rapidly become dangerous and confusing. A combination of increasing experience with outbreaks and genome-sequencing technology now means the pathogen can often be identified within days. But for some of the most frightening viral pathogens, the originating hosts and possible vectors often remain obscure. Babayanet al.took sequence data from more than 500 single-stranded RNA viruses (see the Perspective by Woolhouse) and used machine-learning algorithms to extract evolutionary signals imprinted in the virus sequence that offer information about its original hosts and if an arthropod vector, and what type, plays a part in the virus's natural ecology.Science, this issue p.577; see also p.524
Multidisciplinary, Arthropod Vectors, bats, bat, Genome, Viral, Genomics, Biodiversity, Communicable Diseases, Emerging, Evolution, Molecular, Machine Learning, RNA Virus Infections, Chiroptera, Epidemiological Monitoring, Host-Pathogen Interactions, Mammalia, Animals, Humans, RNA Viruses, Animalia, Chordata, Disease Reservoirs
Multidisciplinary, Arthropod Vectors, bats, bat, Genome, Viral, Genomics, Biodiversity, Communicable Diseases, Emerging, Evolution, Molecular, Machine Learning, RNA Virus Infections, Chiroptera, Epidemiological Monitoring, Host-Pathogen Interactions, Mammalia, Animals, Humans, RNA Viruses, Animalia, Chordata, Disease Reservoirs
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