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• W1968163522 endingPage "e1003254" @default.
• W1968163522 startingPage "e1003254" @default.
• W1968163522 abstract "Despite environmental, social and ecological dependencies, emergence of zoonotic viruses in human populations is clearly also affected by genetic factors which determine cross-species transmission potential. RNA viruses pose an interesting case study given their mutation rates are orders of magnitude higher than any other pathogen – as reflected by the recent emergence of SARS and Influenza for example. Here, we show how feature selection techniques can be used to reliably classify viral sequences by host species, and to identify the crucial minority of host-specific sites in pathogen genomic data. The variability in alleles at those sites can be translated into prediction probabilities that a particular pathogen isolate is adapted to a given host. We illustrate the power of these methods by: 1) identifying the sites explaining SARS coronavirus differences between human, bat and palm civet samples; 2) showing how cross species jumps of rabies virus among bat populations can be readily identified; and 3) de novo identification of likely functional influenza host discriminant markers." @default.
• W1968163522 created "2016-06-24" @default.
• W1968163522 creator A5011273446 @default.
• W1968163522 creator A5016728141 @default.
• W1968163522 date "2013-10-10" @default.
• W1968163522 modified "2023-10-12" @default.
• W1968163522 title "Feature Selection Methods for Identifying Genetic Determinants of Host Species in RNA Viruses" @default.
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• W1968163522 doi "https://doi.org/10.1371/journal.pcbi.1003254" @default.
• W1968163522 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3794897" @default.
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• W1968163522 hasPublicationYear "2013" @default.
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