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{"title"=>"Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin", "type"=>"journal", "authors"=>[{"first_name"=>"Austin G.", "last_name"=>"Meyer", "scopus_author_id"=>"55535876500"}, {"first_name"=>"Claus O.", "last_name"=>"Wilke", "scopus_author_id"=>"7005107626"}], "year"=>2015, "source"=>"PLoS Pathogens", "identifiers"=>{"pmid"=>"26020774", "sgr"=>"84930367860", "scopus"=>"2-s2.0-84930367860", "isbn"=>"1553-7374 (Electronic)\\r1553-7366 (Linking)", "doi"=>"10.1371/journal.ppat.1004940", "pui"=>"604704931", "issn"=>"15537374"}, "id"=>"1a54cbe1-1202-3331-8ba8-f0a46db7dfb6", "abstract"=>"We have carried out a comprehensive analysis of the determinants of human influenza A H3 hemagglutinin evolution. We consider three distinct predictors of evolutionary variation at individual sites: solvent accessibility (as a proxy for protein fold stability and/or conservation), Immune Epitope Database (IEDB) epitope sites (as a proxy for host immune bias), and proximity to the receptor-binding region (as a proxy for one of the functions of hemagglutinin-to bind sialic acid). Individually, these quantities explain approximately 15% of the variation in site-wise dN/dS. In combination, solvent accessibility and proximity explain 32% of the variation in dN/dS; incorporating IEDB epitope sites into the model adds only an additional 2 percentage points. Thus, while solvent accessibility and proximity perform largely as independent predictors of evolutionary variation, they each overlap with the epitope-sites predictor. Furthermore, we find that the historical H3 epitope sites, which date back to the 1980s and 1990s, only partially overlap with the experimental sites from the IEDB, and display similar overlap in predictive power when combined with solvent accessibility and proximity. We also find that sites with dN/dS > 1, i.e., the sites most likely driving seasonal immune escape, are not correctly predicted by either historical or IEDB epitope sites, but only by proximity to the receptor-binding region. In summary, a simple geometric model of HA evolution outperforms a model based on epitope sites. These results suggest that either the available epitope sites do not accurately represent the true influenza antigenic sites or that host immune bias may be less important for influenza evolution than commonly thought.", "link"=>"http://www.mendeley.com/research/geometric-constraints-dominate-antigenic-evolution-influenza-h3n2-hemagglutinin", "reader_count"=>37, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>10, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>12, "Student > Master"=>5, "Student > Bachelor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>2, "Librarian"=>1, "Researcher"=>10, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>12, "Student > Master"=>5, "Student > Bachelor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Biochemistry, Genetics and Molecular Biology"=>9, "Agricultural and Biological Sciences"=>18, "Medicine and Dentistry"=>3, "Veterinary Science and Veterinary Medicine"=>1, "Chemistry"=>1, "Computer Science"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>3}, "Chemistry"=>{"Chemistry"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>18}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>9}, "Unspecified"=>{"Unspecified"=>3}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Canada"=>1, "Korea (South)"=>1, "United States"=>3, "United Kingdom"=>1}, "group_count"=>0}

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• http://doi.org/10.1038/nrg.2015.18
• http://doi.org/10.1093/ve/vev025
• http://doi.org/10.1371/journal.pbio.1002452
• http://doi.org/10.1038/s41598-018-28706-1
• http://doi.org/10.1002/prot.25034
• http://doi.org/10.1016/j.vaccine.2016.10.024
• http://doi.org/10.1038/srep19176
• http://doi.org/10.1111/irv.12458
• http://doi.org/10.1016/j.tim.2017.09.001
• http://doi.org/10.1093/ve/vew026
• http://doi.org/10.1038/nrmicro.2017.118
• http://doi.org/10.1016/j.tim.2017.09.004
• http://doi.org/10.1098/rsif.2015.0579
• http://doi.org/10.1007/s00239-017-9791-y
• http://doi.org/10.1016/j.meegid.2016.06.029
• http://doi.org/10.1186/s12859-018-2283-2
• http://doi.org/10.7717/peerj.3391
• http://doi.org/10.1128/JVI.01408-15
• http://doi.org/10.1038/s41598-019-42614-y
• http://doi.org/10.7554/eLife.18491
• http://doi.org/10.1093/ve/vev006
• http://doi.org/10.1093/protein/gzw017
• http://doi.org/10.1016/j.vaccine.2016.07.015

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• 4710376
• 4726036

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• {"id"=>"603993690227408896", "text"=>"A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http://t.co/YoU2ioF304", "created_at"=>"2015-05-28T18:38:12Z", "user"=>"PLOSPathogens", "user_name"=>"PLOS Pathogens", "user_profile_image"=>"http://pbs.twimg.com/profile_images/459394339945197568/BuJQyL0D_normal.jpeg"}
• {"id"=>"603994784676503553", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-28T18:42:33Z", "user"=>"austingmeyer", "user_name"=>"Austin Meyer", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2991560016/c3a888349dcd78929944c724b321c38c_normal.png"}
• {"id"=>"603994936715816960", "text"=>"Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @austingmeyer", "created_at"=>"2015-05-28T18:43:09Z", "user"=>"ClausWilke", "user_name"=>"Claus Wilke", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000314872884/a9c3e4574b10faf265e0fda9121cf994_normal.jpeg"}
• {"id"=>"603995101329666048", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-28T18:43:48Z", "user"=>"ClausWilke", "user_name"=>"Claus Wilke", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000314872884/a9c3e4574b10faf265e0fda9121cf994_normal.jpeg"}
• {"id"=>"603998406290243584", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-28T18:56:56Z", "user"=>"austingmeyer", "user_name"=>"Austin Meyer", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2991560016/c3a888349dcd78929944c724b321c38c_normal.png"}
• {"id"=>"604002430699884544", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-28T19:12:55Z", "user"=>"DuckSwabber", "user_name"=>"Michelle Wille", "user_profile_image"=>"http://pbs.twimg.com/profile_images/431446000352260096/oCHl-p1G_normal.jpeg"}
• {"id"=>"604020121187704832", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-28T20:23:13Z", "user"=>"FoxandtheFlu", "user_name"=>"Spencer Fox", "user_profile_image"=>"http://pbs.twimg.com/profile_images/447806746107449344/dl31Wwf4_normal.jpeg"}
• {"id"=>"604026496844435456", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-28T20:48:33Z", "user"=>"jplotkin", "user_name"=>"Joshua B. Plotkin", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1848769382/josh3_normal.jpg"}
• {"id"=>"604036114530373632", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-28T21:26:46Z", "user"=>"ESWIRigaconfere", "user_name"=>"ESWI ", "user_profile_image"=>"http://pbs.twimg.com/profile_images/513069714432458752/RSEA3jzS_normal.jpeg"}
• {"id"=>"604039335092953088", "text"=>"Great new paper by @austingmeyer and @ClausWilke on influence of geometric constraints on flu evolution! http://t.co/ZuVVOmvWkZ", "created_at"=>"2015-05-28T21:39:34Z", "user"=>"StephSpiel", "user_name"=>"Stephanie Spielman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/462981196297670656/y7dG4Sy__normal.jpeg"}
• {"id"=>"604040138067312640", "text"=>"RT @StephSpiel: Great new paper by @austingmeyer and @ClausWilke on influence of geometric constraints on flu evolution! http://t.co/ZuVVOm…", "created_at"=>"2015-05-28T21:42:46Z", "user"=>"ClausWilke", "user_name"=>"Claus Wilke", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000314872884/a9c3e4574b10faf265e0fda9121cf994_normal.jpeg"}
• {"id"=>"604041406529675264", "text"=>"RT @StephSpiel: Great new paper by @austingmeyer and @ClausWilke on influence of geometric constraints on flu evolution! http://t.co/ZuVVOm…", "created_at"=>"2015-05-28T21:47:48Z", "user"=>"austingmeyer", "user_name"=>"Austin Meyer", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2991560016/c3a888349dcd78929944c724b321c38c_normal.png"}
• {"id"=>"604050821706293249", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-28T22:25:13Z", "user"=>"ESCVirology", "user_name"=>"ESCV Virology", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2636369813/ad76fb69777c4f971d69ec8e9b40e1e3_normal.jpeg"}
• {"id"=>"604051429951696896", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-28T22:27:38Z", "user"=>"trvrb", "user_name"=>"Trevor Bedford", "user_profile_image"=>"http://pbs.twimg.com/profile_images/532254561386262528/gHX_F_KC_normal.png"}
• {"id"=>"604086694833315840", "text"=>"幾何拘束イフルザH3N2ヘマグルチニ抗原進化支配 http://t.co/ViOLuqeYit 個サト進化バリシ3明確予測考:溶媒アクセシビリテ蛋白質折安定保全プロキシ)免疫エピトプデタベスIEDB)エピトプサトプロキシホスト免疫バス)受容体結合領域近赤血球凝集素機能1対プロキシ", "created_at"=>"2015-05-29T00:47:46Z", "user"=>"abbrabot", "user_name"=>"ひらがなは各自補うこと", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1210855216/omu-gai_normal.jpg"}
• {"id"=>"604092879783485440", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-29T01:12:20Z", "user"=>"evolcoop", "user_name"=>"Sam Diaz-Munoz", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1725131520/sam_profile_normal.JPG"}
• {"id"=>"604137757716267009", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-29T04:10:40Z", "user"=>"self_adjoint", "user_name"=>"mehmet umut caglar", "user_profile_image"=>"http://pbs.twimg.com/profile_images/534219075644174337/Zo-pv13I_normal.jpeg"}
• {"id"=>"604179277953781760", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-29T06:55:39Z", "user"=>"EstherBlanco01", "user_name"=>"Esther Blanco", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2412676485/jlrzlay0eggkqbjv8xwn_normal.jpeg"}
• {"id"=>"604208972472696832", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-29T08:53:39Z", "user"=>"jnaraghwani", "user_name"=>"Jayna Raghwani", "user_profile_image"=>"http://pbs.twimg.com/profile_images/571642430714179584/CwL8qPLL_normal.jpeg"}
• {"id"=>"604257192368279552", "text"=>"RT @ClausWilke: Now out in @PLOSPathogens: Geometric Constraints Dominate the Antigenic Evolution of Influenza HA http://t.co/mI523SyadU @a…", "created_at"=>"2015-05-29T12:05:15Z", "user"=>"PabloRMurcia", "user_name"=>"Pablo Murcia", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000824950163/98bf1f175dd9e8ae25b986e0ef03fe1f_normal.png"}
• {"id"=>"604274173897113601", "text"=>"RT @PLOSPathogens: A comprehensive analysis of determinants of human influenza A H3 hemagglutinin evolution-- with interesting results http…", "created_at"=>"2015-05-29T13:12:44Z", "user"=>"too07", "user_name"=>"Young-bin YIM", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1428705720/___normal.JPG"}
• {"id"=>"605074955634483200", "text"=>"RT @StephSpiel: Great new paper by @austingmeyer and @ClausWilke on influence of geometric constraints on flu evolution! http://t.co/ZuVVOm…", "created_at"=>"2015-05-31T18:14:45Z", "user"=>"dariyasydykova", "user_name"=>"Dariya Sydykova", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000315217328/f9d8aa4cb2c6a2b429c6dc8092ae37bb_normal.jpeg"}
• {"id"=>"605076523985436673", "text"=>"RT @StephSpiel: Great new paper by @austingmeyer and @ClausWilke on influence of geometric constraints on flu evolution! http://t.co/ZuVVOm…", "created_at"=>"2015-05-31T18:20:59Z", "user"=>"Aashiq_UT", "user_name"=>"Aashiq H Kachroo", "user_profile_image"=>"http://pbs.twimg.com/profile_images/460506425999888385/JV78Tzt-_normal.jpeg"}
• {"id"=>"611650966354587648", "text"=>"@MeyerBjoern @trvrb @ClausWilke it's true in flu hemagglutinin... http://t.co/V2KMSsENZP", "created_at"=>"2015-06-18T21:45:28Z", "user"=>"austingmeyer", "user_name"=>"Austin Meyer", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2991560016/c3a888349dcd78929944c724b321c38c_normal.png"}
• {"id"=>"619952722272391168", "text"=>"An #influenza #pandemic is only a couple of mutations away. Or is it? http://t.co/K79nAfhPa8 @PLOSPathogens", "created_at"=>"2015-07-11T19:33:41Z", "user"=>"malinyoung", "user_name"=>"Malin Young", "user_profile_image"=>"http://pbs.twimg.com/profile_images/613869431026925568/EAGwufFC_normal.jpg"}
• {"id"=>"627049808818237441", "text"=>"Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin http://t.co/iatgtPpVp7 http://t.co/rmsylMmHAq", "created_at"=>"2015-07-31T09:34:59Z", "user"=>"Virus_Evolution", "user_name"=>"Virus Evolution", "user_profile_image"=>"http://pbs.twimg.com/profile_images/532202513915604993/vUq_dz52_normal.jpeg"}
• {"id"=>"627228852654243841", "text"=>"RT @Virus_Evolution: Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin http://t.co/iatgtPpVp7 http://t…", "created_at"=>"2015-07-31T21:26:26Z", "user"=>"ClausWilke", "user_name"=>"Claus Wilke", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000314872884/a9c3e4574b10faf265e0fda9121cf994_normal.jpeg"}
• {"id"=>"627247619518009344", "text"=>"RT @Virus_Evolution: Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin http://t.co/iatgtPpVp7 http://t…", "created_at"=>"2015-07-31T22:41:00Z", "user"=>"elbruger13", "user_name"=>"Eric Bruger", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000303146956/3acc5c1d15afacc7d5335f793f77d742_normal.jpeg"}
• {"id"=>"627264560672714752", "text"=>"RT @Virus_Evolution: Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin http://t.co/iatgtPpVp7 http://t…", "created_at"=>"2015-07-31T23:48:19Z", "user"=>"StephSpiel", "user_name"=>"Stephanie Spielman", "user_profile_image"=>"http://pbs.twimg.com/profile_images/462981196297670656/y7dG4Sy__normal.jpeg"}
• {"id"=>"632348278214914048", "text"=>"RT @Virus_Evolution: Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin http://t.co/iatgtPpVp7 http://t…", "created_at"=>"2015-08-15T00:29:12Z", "user"=>"austingmeyer", "user_name"=>"Austin Meyer", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2991560016/c3a888349dcd78929944c724b321c38c_normal.png"}
• {"id"=>"632354693184819202", "text"=>"RT @Virus_Evolution: Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin http://t.co/iatgtPpVp7 http://t…", "created_at"=>"2015-08-15T00:54:42Z", "user"=>"weitzlab", "user_name"=>"Joshua Weitz", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1793262475/weitz_crop_med_v2_normal.jpg"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/2086799"], "description"=>"<p>The sites shown in purple are those identified by Koel et al. 2013 [<a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004940#ppat.1004940.ref021\" target=\"_blank\">21</a>] to be critical for antigenic cluster transitions. Only one of these sites has a <i>dN</i>/<i>dS</i> significantly above one, site 145. The sites shown in red are those that our geometrical model predicts to have <i>dN</i>/<i>dS</i> > 1. (Half of those sites have observed <i>dN</i>/<i>dS</i> > 1.) Note that our model predicts only sites on the basal side of sialic acid to be under positive selection, since our reference point for proximity is site 224. Site 145, the only purple site under positive selection, is also the only purple site on the basal side of sialic acid.</p>", "links"=>[], "tags"=>["IEDB epitope sites", "Geometric Constraints Dominate", "Influenza H 3N Hemagglutinin", "epitope sites", "proximity", "2 percentage points", "accessibility", "influenza antigenic sites", "variation", "H 3 epitope sites", "ha", "H 3 hemagglutinin evolution"], "article_id"=>1429522, "categories"=>["Biological Sciences"], "users"=>["Austin G. Meyer", "Claus O. Wilke"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1004940.g004", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sites_identified_by_Koel_et_al_2013_and_those_predicted_to_have_dN_dS_1_/1429522", "title"=>"Sites identified by Koel et al. 2013 and those predicted to have <i>dN</i>/<i>dS</i> > 1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-28 04:07:53"}
• {"files"=>["https://ndownloader.figshare.com/files/2086800"], "description"=>"<p><i>R</i>² is the proportion of variation in <i>dN</i>/<i>dS</i> explained by the specified model. RSE is the residual standard error of the linear model. cvRSE₁₀ is the cross validated residual standard error calculated by 10-fold cross validation. cvRSE_loo is the cross validated residual standard error calculated by leave-one-out cross validation.</p><p>Predictive performance of each linear model considered.</p>", "links"=>[], "tags"=>["IEDB epitope sites", "Geometric Constraints Dominate", "Influenza H 3N Hemagglutinin", "epitope sites", "proximity", "2 percentage points", "accessibility", "influenza antigenic sites", "variation", "H 3 epitope sites", "ha", "H 3 hemagglutinin evolution"], "article_id"=>1429523, "categories"=>["Biological Sciences"], "users"=>["Austin G. Meyer", "Claus O. Wilke"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1004940.t001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Predictive_performance_of_each_linear_model_considered_/1429523", "title"=>"Predictive performance of each linear model considered.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-05-28 04:07:53"}
• {"files"=>["https://ndownloader.figshare.com/files/2086809", "https://ndownloader.figshare.com/files/2086810", "https://ndownloader.figshare.com/files/2086811", "https://ndownloader.figshare.com/files/2086812"], "description"=>"<div><p>We have carried out a comprehensive analysis of the determinants of human influenza A H3 hemagglutinin evolution. We consider three distinct predictors of evolutionary variation at individual sites: solvent accessibility (as a proxy for protein fold stability and/or conservation), Immune Epitope Database (IEDB) epitope sites (as a proxy for host immune bias), and proximity to the receptor-binding region (as a proxy for one of the functions of hemagglutinin-to bind sialic acid). Individually, these quantities explain approximately 15% of the variation in site-wise <i>dN/dS</i>. In combination, solvent accessibility and proximity explain 32% of the variation in <i>dN/dS</i>; incorporating IEDB epitope sites into the model adds only an additional 2 percentage points. Thus, while solvent accessibility and proximity perform largely as independent predictors of evolutionary variation, they each overlap with the epitope-sites predictor. Furthermore, we find that the historical H3 epitope sites, which date back to the 1980s and 1990s, only partially overlap with the experimental sites from the IEDB, and display similar overlap in predictive power when combined with solvent accessibility and proximity. We also find that sites with <i>dN/dS</i> > 1, i.e., the sites most likely driving seasonal immune escape, are not correctly predicted by either historical or IEDB epitope sites, but only by proximity to the receptor-binding region. In summary, a simple geometric model of HA evolution outperforms a model based on epitope sites. These results suggest that either the available epitope sites do not accurately represent the true influenza antigenic sites or that host immune bias may be less important for influenza evolution than commonly thought.</p></div>", "links"=>[], "tags"=>["IEDB epitope sites", "Geometric Constraints Dominate", "Influenza H 3N Hemagglutinin", "epitope sites", "proximity", "2 percentage points", "accessibility", "influenza antigenic sites", "variation", "H 3 epitope sites", "ha", "H 3 hemagglutinin evolution"], "article_id"=>1429532, "categories"=>["Biological Sciences"], "users"=>["Austin G. Meyer", "Claus O. Wilke"], "doi"=>["https://dx.doi.org/10.1371/journal.ppat.1004940.s001", "https://dx.doi.org/10.1371/journal.ppat.1004940.s002", "https://dx.doi.org/10.1371/journal.ppat.1004940.s003", "https://dx.doi.org/10.1371/journal.ppat.1004940.s004"], "stats"=>{"downloads"=>2, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Geometric_Constraints_Dominate_the_Antigenic_Evolution_of_Influenza_H3N2_Hemagglutinin_/1429532", "title"=>"Geometric Constraints Dominate the Antigenic Evolution of Influenza H3N2 Hemagglutinin", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-05-28 04:07:53"}
• {"files"=>["https://ndownloader.figshare.com/files/2086793"], "description"=>"<p>(A) Each site in the protein structure is colored according to its evolutionary rate <i>dN</i>/<i>dS</i>. Hot colors represent high <i>dN</i>/<i>dS</i> (positive selection) while cool colors represent low <i>dN</i>/<i>dS</i> (purifying selection). (B) Each site in the protein structure is colored according to the <i>dN</i>/<i>dS</i>–distance correlation obtained when distances are calculated relative to that site. Hot colors represent positive correlations while cool colors represent negative correlations. Thus, distances from sites that are redder are better positive predictors of the evolutionary rates in the protein than are distances from bluer sites; distances from blue sites are actually anti-correlated with evolutionary rate. Distances from sites that are colored green have essentially no predictive ability.</p>", "links"=>[], "tags"=>["IEDB epitope sites", "Geometric Constraints Dominate", "Influenza H 3N Hemagglutinin", "epitope sites", "proximity", "2 percentage points", "accessibility", "influenza antigenic sites", "variation", "H 3 epitope sites", "ha", "H 3 hemagglutinin evolution"], "article_id"=>1429516, "categories"=>["Biological Sciences"], "users"=>["Austin G. Meyer", "Claus O. Wilke"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1004940.g001", "stats"=>{"downloads"=>0, "page_views"=>178, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolutionary_rate_variation_along_the_hemagglutinin_structure_/1429516", "title"=>"Evolutionary-rate variation along the hemagglutinin structure.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-28 04:07:53"}
• {"files"=>["https://ndownloader.figshare.com/files/2086794"], "description"=>"<p>The height of each bar represents the coefficient of determination (<i>R</i>²) for a linear model consisting of the stated predictor variables. The historical epitope sites from Bush 1999 [<a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1004940#ppat.1004940.ref004\" target=\"_blank\">4</a>] (yellow bar on the left) are the single best predictor of evolutionary rate variation. However, a model using two predictors that each have a clear biophysical meaning (solvent exposure, proximity to receptor-binding region) explains almost twice the variation in <i>dN</i>/<i>dS</i> (yellow bar on the right).</p>", "links"=>[], "tags"=>["IEDB epitope sites", "Geometric Constraints Dominate", "Influenza H 3N Hemagglutinin", "epitope sites", "proximity", "2 percentage points", "accessibility", "influenza antigenic sites", "variation", "H 3 epitope sites", "ha", "H 3 hemagglutinin evolution"], "article_id"=>1429517, "categories"=>["Biological Sciences"], "users"=>["Austin G. Meyer", "Claus O. Wilke"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1004940.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Proportion_of_variance_in_dN_dS_explained_by_different_linear_models_/1429517", "title"=>"Proportion of variance in <i>dN</i>/<i>dS</i> explained by different linear models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-28 04:07:53"}
• {"files"=>["https://ndownloader.figshare.com/files/2086795"], "description"=>"<p>(A) Only epitope status according to the historical definition is used as predictor variable. (B) Historical epitope sites and RSA are used as predictor variables. (C) Only epitope status according to the IEDB non-linear epitope data is used as predictor variable. (D) IEDB epitope sites and RSA are used as predictor variables. (E) Only proximity to the sialic acid-binding region (measured as 1/Distance to Residue 224) is used as predictor variable. (F) Proximity and RSA are used as predictor variables. Individual sites with <i>dN</i>/<i>dS</i> > 1 are predicted correctly only if the linear model includes the 1/Distance predictor. However, in all cases, adding the RSA predictor significantly improves the model predictions.</p>", "links"=>[], "tags"=>["IEDB epitope sites", "Geometric Constraints Dominate", "Influenza H 3N Hemagglutinin", "epitope sites", "proximity", "2 percentage points", "accessibility", "influenza antigenic sites", "variation", "H 3 epitope sites", "ha", "H 3 hemagglutinin evolution"], "article_id"=>1429518, "categories"=>["Biological Sciences"], "users"=>["Austin G. Meyer", "Claus O. Wilke"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1004940.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Observed_dN_dS_vs_predicted_dN_dS_for_different_predictive_linear_models_/1429518", "title"=>"Observed <i>dN</i>/<i>dS</i> vs. predicted <i>dN</i>/<i>dS</i> for different predictive linear models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-05-28 04:07:53"}

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• {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
• {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"2"}
• {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
• {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
• {"unique-ip"=>"2", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
• {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
• {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
• {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
• {"unique-ip"=>"7", "full-text"=>"5", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
• {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
• {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
• {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
• {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
• {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
• {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
• {"unique-ip"=>"9", "full-text"=>"9", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
• {"unique-ip"=>"5", "full-text"=>"5", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}

F1000Prime