Information Processing in Social Insect Networks
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{"title"=>"Information processing in social insect networks", "type"=>"journal", "authors"=>[{"first_name"=>"James S.", "last_name"=>"Waters", "scopus_author_id"=>"36901087700"}, {"first_name"=>"Jennifer H.", "last_name"=>"Fewell", "scopus_author_id"=>"7005358572"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"22815740", "doi"=>"10.1371/journal.pone.0040337", "sgr"=>"84864005162", "isbn"=>"9781450314626", "scopus"=>"2-s2.0-84864005162", "issn"=>"19326203", "pui"=>"365274136"}, "id"=>"c63bb813-3797-3565-bda6-bf86f654eb23", "abstract"=>"Investigating local-scale interactions within a network makes it possible to test hypotheses about the mechanisms of global network connectivity and to ask whether there are general rules underlying network function across systems. Here we use motif analysis to determine whether the interactions within social insect colonies resemble the patterns exhibited by other animal associations or if they exhibit characteristics of biological regulatory systems. Colonies exhibit a predominance of feed-forward interaction motifs, in contrast to the densely interconnected clique patterns that characterize human interaction and animal social networks. The regulatory motif signature supports the hypothesis that social insect colonies are shaped by selection for network patterns that integrate colony functionality at the group rather than individual level, and demonstrates the utility of this approach for analysis of selection effects on complex systems across biological levels of organization.", "link"=>"http://www.mendeley.com/research/information-processing-social-insect-networks-2", "reader_count"=>146, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>9, "Researcher"=>25, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>56, "Student > Postgraduate"=>6, "Student > Master"=>21, "Other"=>1, "Student > Bachelor"=>10, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>5, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>9, "Researcher"=>25, "Student > Doctoral Student"=>7, "Student > Ph. D. Student"=>56, "Student > Postgraduate"=>6, "Student > Master"=>21, "Other"=>1, "Student > Bachelor"=>10, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>5, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>11, "Agricultural and Biological Sciences"=>74, "Arts and Humanities"=>1, "Philosophy"=>1, "Business, Management and Accounting"=>1, "Computer Science"=>32, "Engineering"=>2, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>1, "Mathematics"=>2, "Medicine and Dentistry"=>2, "Neuroscience"=>2, "Design"=>1, "Physics and Astronomy"=>6, "Psychology"=>3, "Social Sciences"=>4}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Social Sciences"=>{"Social Sciences"=>4}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Psychology"=>{"Psychology"=>3}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>11}, "Environmental Science"=>{"Environmental Science"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>2}, "Neuroscience"=>{"Neuroscience"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>74}, "Computer Science"=>{"Computer Science"=>32}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Philosophy"=>{"Philosophy"=>1}}, "reader_count_by_country"=>{"Hungary"=>1, "United States"=>7, "Japan"=>1, "United Kingdom"=>3, "Switzerland"=>1, "Spain"=>1, "India"=>1, "Turkey"=>1, "China"=>3, "Brazil"=>1, "Poland"=>1, "Israel"=>1, "Germany"=>2}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/608848"], "description"=>"<p>Triad significance profiles compare the characteristic network motifs across a diverse range of network types and sizes by plotting standardized Z-scores which quantify the extent to which each subgraph is observed more or less frequently than expected in networks of a similar size and global structure but with randomized edge connections. The observed <i>P. californicus</i> social insect networks exhibit a distinct pattern of social regulatory structure combining elements found in previously identified major network superfamilies <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0040337#pone.0040337-Milo2\" target=\"_blank\">[22]</a>.</p>", "links"=>[], "tags"=>["Computational biology", "ecology", "neuroscience", "Evolutionary biology"], "article_id"=>279341, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.g003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Social_regulatory_networks_/279341", "title"=>"Social regulatory networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-16 02:35:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/608682"], "description"=>"<p>(<b>A</b>) The development of a directed network of interactions between workers in a single <i>P. californicus</i> colony over a period of 60 s. Nodes represent individual workers or queens within a colony and arrows represent interactions between individuals. (<b>B</b>) Example <i>P. californicus</i> interaction network based on 26 s of colony behavior. (<b>C</b>) Photograph of queens and workers within a seed harvester colony; individuals have been painted with unique color combinations to track their interactions.</p>", "links"=>[], "tags"=>["Computational biology", "ecology", "neuroscience", "Evolutionary biology"], "article_id"=>279176, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.g001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ant_colony_interaction_networks_/279176", "title"=>"Ant colony interaction networks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-16 02:32:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/609024"], "description"=>"<p>This table summarizes global-scale network statistics for the twelve observed <i>P. californicus</i> interaction networks.</p>", "links"=>[], "tags"=>["Computational biology", "ecology", "neuroscience", "Evolutionary biology"], "article_id"=>279523, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.t001", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_statistics_for_P_californicus_interaction_networks_/279523", "title"=>"Summary statistics for <i>P. californicus</i> interaction networks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-16 02:38:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/608993"], "description"=>"<p>(1) This is the OLS-estimated slope for the relationship describing how the number of nodes with a given number of out-degree edges scales with out-degree. The data (x) were transformed prior to regression according to log<sub>10</sub>(x+1). The absolute value of the slope is an estimate for the degree distribution power law exponent (alpha).</p>", "links"=>[], "tags"=>["out-degree", "scaling"], "article_id"=>279490, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.t002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_out_degree_scaling_analysis_/279490", "title"=>"Summary of out-degree scaling analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-16 02:38:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/608966"], "description"=>"<p>(2) This is the OLS-estimated slope for the relationship describing how the number of nodes with a given number of in-degree edges scales with in-degree. The data (x) were transformed prior to regression according to log<sub>10</sub>(x+1). The absolute value of the slope is an estimate for the degree distribution power law exponent (alpha).</p>", "links"=>[], "tags"=>["in-degree", "scaling"], "article_id"=>279472, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.t003", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_out_in_degree_scaling_analysis_/279472", "title"=>"Summary out in-degree scaling analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-16 02:37:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/608936"], "description"=>"<p>This table summarizes the classification of subgraphs as network motifs. (1) The number of observed networks containing each respective subgraph. (2) The number of networks in which the observed density for a subgraph is significantly greater than its density in the random networks and in which the subgraph appears more than once in the observed network. (3) The number of networks in which the average observed density for a subgraph is significantly greater than its density in the random networks and in which the subgraph density is at least one percent in the observed network.</p>", "links"=>[], "tags"=>["motif"], "article_id"=>279438, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.t004", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_motif_analysis_results_/279438", "title"=>"Network motif analysis results.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-16 02:37:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/317726", "https://ndownloader.figshare.com/files/317843", "https://ndownloader.figshare.com/files/317901", "https://ndownloader.figshare.com/files/317987"], "description"=>"<div><p>Investigating local-scale interactions within a network makes it possible to test hypotheses about the mechanisms of global network connectivity and to ask whether there are general rules underlying network function across systems. Here we use motif analysis to determine whether the interactions within social insect colonies resemble the patterns exhibited by other animal associations or if they exhibit characteristics of biological regulatory systems. Colonies exhibit a predominance of feed-forward interaction motifs, in contrast to the densely interconnected clique patterns that characterize human interaction and animal social networks. The regulatory motif signature supports the hypothesis that social insect colonies are shaped by selection for network patterns that integrate colony functionality at the group rather than individual level, and demonstrates the utility of this approach for analysis of selection effects on complex systems across biological levels of organization.</p> </div>", "links"=>[], "tags"=>["networks"], "article_id"=>122731, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0040337.s001", "https://dx.doi.org/10.1371/journal.pone.0040337.s002", "https://dx.doi.org/10.1371/journal.pone.0040337.s003", "https://dx.doi.org/10.1371/journal.pone.0040337.s004"], "stats"=>{"downloads"=>21, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Information_Processing_in_Social_Insect_Networks/122731", "title"=>"Information Processing in Social Insect Networks", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-07-16 00:45:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/608776"], "description"=>"<p>Network motif analysis deconstructs a network into its constituent subgraphs and determines whether any of these local-scale interaction patterns are represented more frequently than expected for a randomized network of the same size. The subgraphs that were identified as significant motifs in our analysis of social insect colony networks are plotted above in a summary histogram with relative frequencies on the left axis. The interaction efficiencies of each subgraph are plotted as a line with units along the right axis. One of the two subgraphs with the highest efficiencies, the feed-forward loop (motif 7), was also the most dominant motif observed across the <i>P. californicus</i> interaction networks. Gray subgraphs were not classified as network motifs, black indicates a subgraph identified as a motif within at least one network, and red indicates the only motif that was identified across the majority of networks.</p>", "links"=>[], "tags"=>["Computational biology", "ecology", "neuroscience", "Evolutionary biology"], "article_id"=>279274, "categories"=>["Biological Sciences", "Neuroscience", "Ecology", "Evolutionary Biology"], "users"=>["James S. Waters", "Jennifer H. Fewell"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0040337.g002", "stats"=>{"downloads"=>0, "page_views"=>36, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_network_motifs_/279274", "title"=>"Distribution of network motifs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-16 02:34:34"}

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Relative Metric

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