{"id":2799,"date":"2016-01-11T20:09:47","date_gmt":"2016-01-11T20:09:47","guid":{"rendered":"http:\/\/www.blopig.com\/blog\/?p=2799"},"modified":"2016-01-11T20:09:47","modified_gmt":"2016-01-11T20:09:47","slug":"network-hubs","status":"publish","type":"post","link":"https:\/\/www.blopig.com\/blog\/2016\/01\/network-hubs\/","title":{"rendered":"Network Hubs"},"content":{"rendered":"<p>Some times real networks contain few nodes that are connected to a large portion of the nodes in the network. These nodes, often called &#8216;hubs&#8217; (or global hubs), can change global properties of the network drastically, for example the length of the shortest path between two nodes can be significantly reduced by their presence.<\/p>\n<p>The presence of hubs in real networks can be easily observed, for example, in flight networks airports such as Heathrow (UK) or Beijing capital IAP (China) have a very large number of incoming and outgoing flights in comparison to all other airports in the world. Now, if in addition to the network there is a partition of the nodes into different groups &#8216;local hubs&#8217; can appear. For example, assume that the political division is a partition of the nodes (airports) into different countries. Then, some capital city airports can be local hubs as they\u00a0have incoming and outgoing\u00a0flights to most other airports in that same\u00a0country. Note that a local hub might not be a global hub.<\/p>\n<p>There are several ways to classify nodes based on different network properties. Take for example, hub nodes and non-hub nodes. One way to classify nodes as hub or non-hub uses the\u00a0<em>participation coefficient<\/em>\u00a0and the\u00a0<em>standardised\u00a0within module degree<\/em>\u00a0(Gimera &amp; \u00a0Amaral, 2005).<\/p>\n<p>Consider a partition of the nodes into <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=N_M&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"N_M\" class=\"latex\" \/> groups. Let <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=k_i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"k_i\" class=\"latex\" \/> be the degree of node <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"i\" class=\"latex\" \/> and <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=k_%7Bis%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"k_{is}\" class=\"latex\" \/> the number of links or edges to other nodes in the same group as node\u00a0<img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"i\" class=\"latex\" \/>. Then, the participation coefficient of node\u00a0<img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"i\" class=\"latex\" \/> is:<\/p>\n<p style=\"text-align: center\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=P_i+%3D+1+-+%5Csum_%7Bs%3D1%7D%5E%7BN_M%7D+k_%7Bis%7D%5E2+%2F+k_i%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"P_i = 1 - &#92;sum_{s=1}^{N_M} k_{is}^2 \/ k_i^2\" class=\"latex\" \/> .<\/p>\n<div class=\"page\" title=\"Page 6\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<p>Note that if node\u00a0<img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"i\" class=\"latex\" \/> is connected only to nodes within its group then, the participation coefficient of node\u00a0<img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"i\" class=\"latex\" \/> is 0. Otherwise if it is connected to nodes uniformly distributed across all groups then the participation coefficient is close to 1 (Gimera &amp; \u00a0Amaral, 2005).<\/p>\n<p>Now, the standardised within module degree:<\/p>\n<p style=\"text-align: center\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=z_i%3D+%28k_i+-+%5Cbar%7Bk%7D_%7Bs_i%7D%29+%2F+%5Csigma_%7Bk_%7Bs_i%7D%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"z_i= (k_i - &#92;bar{k}_{s_i}) \/ &#92;sigma_{k_{s_i}}\" class=\"latex\" \/>,<\/p>\n<p>where <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=s_i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"s_i\" class=\"latex\" \/> is the group node <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=i&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"i\" class=\"latex\" \/> belongs to and\u00a0<span style=\"line-height: 1.5\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_%7Bk_%7Bs_i%7D%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_{k_{s_i}}\" class=\"latex\" \/> is the standard deviation of <img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/s0.wp.com\/latex.php?latex=k&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"k\" class=\"latex\" \/>\u00a0in such group.<\/span><\/p>\n<\/div>\n<\/div>\n<\/div>\n<p>Gimera &amp; \u00a0Amaral (2005) proposed a classification of the nodes of the network based on their corresponding values of the previous statistics. In particular they proposed a heuristic classification of the nodes depicted by the following plot<\/p>\n<div id=\"attachment_288\" style=\"width: 474px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/luisospina.files.wordpress.com\/2016\/01\/screen-shot-2016-01-10-at-19-35-48.png\" rel=\"attachment wp-att-288\"><img data-recalc-dims=\"1\" decoding=\"async\" aria-describedby=\"caption-attachment-288\" loading=\"lazy\" class=\"size-full wp-image-288\" src=\"https:\/\/luisospina.files.wordpress.com\/2016\/01\/screen-shot-2016-01-10-at-19-35-48.png?resize=464%2C470\" alt=\"Image taken from the paper &quot;Functional cartography of complex metabolic networks&quot; by Guimera and Amaral, 2005.\" width=\"464\" height=\"470\" \/><\/a><p id=\"caption-attachment-288\" class=\"wp-caption-text\">Image taken from the paper &#8220;Functional cartography of complex<br \/>metabolic networks&#8221; by Guimera and Amaral, 2005.<\/p><\/div>\n<p>Guimera and Amaral (2005), named regions R1-R4 as non-hub regions and R5-R7 as hub regions. Nodes belonging to: R1 are labelled as ultra-peripheral nodes, R2 as peripheral nodes, R3 as nun-hub connector nodes, R4 as non-hub kinless nodes, R5 as provincial nodes, R6 as connector hubs and R7 as kinless hubs. For more details on this categorisation please see\u00a0Guimera and Amaral (2005).<\/p>\n<p>The previous regions\u00a0give an intuitive classification of network nodes according to\u00a0their connectivity\u00a0under a given partition of the nodes. In particular it gives an easy way to differentiate hub nodes of non-hub nodes. However the classification of the nodes into these seven regions (R1-R7) depends on the initial partition of the nodes.<\/p>\n<div class=\"page\" title=\"Page 93\">\n<div class=\"layoutArea\">\n<div class=\"column\">\n<ol>\n<li>R. Guimer\u00e0, L.A.N. Amaral,\u00a0<em>Functional cartography of complex metabolic networks<\/em>, Nature 433 (2005) 895\u2013900<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Some times real networks contain few nodes that are connected to a large portion of the nodes in the network. These nodes, often called &#8216;hubs&#8217; (or global hubs), can change global properties of the network drastically, for example the length of the shortest path between two nodes can be significantly reduced by their presence. The [&hellip;]<\/p>\n","protected":false},"author":26,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","wikipediapreview_detectlinks":true,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"ngg_post_thumbnail":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"ppma_author":[514],"class_list":["post-2799","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"authors":[{"term_id":514,"user_id":26,"is_guest":0,"slug":"luis","display_name":"Luis Ospina Forero","avatar_url":"https:\/\/secure.gravatar.com\/avatar\/310cef32cd5dac5a383fe35d2e6fa0ed40cb03d0712d2b5a5ef81092db812b3e?s=96&d=mm&r=g","0":null,"1":"","2":"","3":"","4":"","5":"","6":"","7":"","8":""}],"_links":{"self":[{"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/posts\/2799","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/users\/26"}],"replies":[{"embeddable":true,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/comments?post=2799"}],"version-history":[{"count":1,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/posts\/2799\/revisions"}],"predecessor-version":[{"id":2800,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/posts\/2799\/revisions\/2800"}],"wp:attachment":[{"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/media?parent=2799"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/categories?post=2799"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/tags?post=2799"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.blopig.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=2799"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}