Mendeley | Further Information

{"title"=>"Inferring epidemiological parameters from phylogenies using regression-ABC: A comparative study", "type"=>"journal", "authors"=>[{"first_name"=>"Emma", "last_name"=>"Saulnier", "scopus_author_id"=>"57193809683"}, {"first_name"=>"Olivier", "last_name"=>"Gascuel", "scopus_author_id"=>"7003870805"}, {"first_name"=>"Samuel", "last_name"=>"Alizon", "scopus_author_id"=>"16027863300"}], "year"=>2017, "source"=>"PLoS Computational Biology", "identifiers"=>{"issn"=>"15537358", "isbn"=>"1111111111", "pmid"=>"28263987", "scopus"=>"2-s2.0-85016816403", "pui"=>"615171579", "doi"=>"10.1371/journal.pcbi.1005416", "sgr"=>"85016816403"}, "id"=>"b9889ece-aeec-3ac9-a4a9-bdda48577d34", "abstract"=>"Author summary Given the rapid evolution of many pathogens, analysing their genomes by means of phylogenies can inform us about how they spread. This is the focus of the field known as “phylodynamics”. Most existing methods inferring epidemiological parameters from virus phylogenies are limited by the difficulty of handling complex likelihood functions, which commonly incorporate latent variables. Here, we use an alternative method known as regression-based Approximate Bayesian Computation (ABC), which circumvents this problem by using simulations and dataset comparisons. Since phylogenies are difficult to compare to one another, we introduce many summary statistics to describe them and take advantage of current machine learning techniques able to perform variable selection. We show that the accuracy we reach is comparable to that of existing methods. This accuracy increases with phylogeny size and can even be higher than that of existing methods for some parameters. Overall, regression-based ABC opens new perspectives to infer epidemiological parameters from large phylogenies.", "link"=>"http://www.mendeley.com/research/inferring-epidemiological-parameters-phylogenies-using-regressionabc-comparative-study", "reader_count"=>29, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>13, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>1, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>13, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>1, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>3, "Mathematics"=>1, "Medicine and Dentistry"=>4, "Agricultural and Biological Sciences"=>6, "Veterinary Science and Veterinary Medicine"=>2, "Computer Science"=>1, "Decision Sciences"=>1, "Immunology and Microbiology"=>3}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>6}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>2}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>2}}, "reader_count_by_country"=>{"United States"=>1}, "group_count"=>0}

CrossRef

• http://doi.org/10.1093/bioinformatics/bty867
• http://doi.org/10.1186/s12862-018-1210-5
• http://doi.org/10.1002/ece3.5185
• http://doi.org/10.1016/j.epidem.2019.100349
• http://doi.org/10.1002/wics.1486
• http://doi.org/10.1002/eap.1873
• http://doi.org/10.24072/pci.evolbiol.100117
• http://doi.org/10.1038/s41598-020-78900-3
• http://doi.org/10.3389/fmicb.2018.00343
• http://doi.org/10.1371/journal.pbio.2003815
• http://doi.org/10.1016/j.mbs.2020.108503
• http://doi.org/10.1186/s13567-019-0692-5
• http://doi.org/10.1093/sysbio/syy048
• http://doi.org/10.1016/j.epidem.2020.100398

Scopus | Further Information

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• {"unique-ip"=>"15", "full-text"=>"14", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"3"}
• {"unique-ip"=>"12", "full-text"=>"13", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}
• {"unique-ip"=>"15", "full-text"=>"20", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2020", "month"=>"5"}
• {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"6"}
• {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"29", "cited-by"=>"0", "year"=>"2020", "month"=>"7"}
• {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"8"}
• {"unique-ip"=>"8", "full-text"=>"5", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"9"}
• {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"10"}
• {"unique-ip"=>"7", "full-text"=>"4", "pdf"=>"5", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"11"}
• {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"12"}
• {"unique-ip"=>"8", "full-text"=>"10", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2021", "month"=>"1"}
• {"unique-ip"=>"2", "full-text"=>"2", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2021", "month"=>"2"}

F1000Prime