ArticlePLoS computational biology2013
Feature selection methods for identifying genetic determinants of host species in RNA viruses.
Article in PLoS computational biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Influenza virus genotype to phenotype predictions through machine learning: a systematic review.Emerging microbes & infections · 2021Pooled it
- Predictive phage therapy forProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Predicting host species susceptibility to influenza viruses and coronaviruses using genome data and machine learning: a scoping review.Frontiers in veterinary science · 2024Article
- Application of machine learning in bacteriophage research.BMC microbiology · 2021Review
- Immuno-epidemiology and pathophysiology of coronavirus disease 2019 (COVID-19).Journal of molecular medicine (Berlin, Germany) · 2020Review
- Fermented Seeds ("Zgougou") from Aleppo Pine as a Novel Source of Potentially Probiotic Lactic Acid Bacteria.Microorganisms · 2019Article
- A guide to machine learning for bacterial host attribution using genome sequence data.Microbial genomics · 2019Article
- Host Taxon Predictor - A Tool for Predicting Taxon of the Host of a Newly Discovered Virus.Scientific reports · 2019Article
- Existing Host Range Mutations Constrain Further Emergence of RNA Viruses.Journal of virology · 2019Article
- Comparative studies of alignment, alignment-free and SVM based approaches for predicting the hosts of viruses based on viral sequences.Scientific reports · 2018Article
- Lineage structure of Streptococcus pneumoniae may be driven by immune selection on the groEL heat-shock protein.Scientific reports · 2017Article
- K-Pax2: Bayesian identification of cluster-defining amino acid positions in large sequence datasets.Microbial genomics · 2015Article
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2 authors.
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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.
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