{"id":37,"date":"2025-03-01T19:23:59","date_gmt":"2025-03-01T19:23:59","guid":{"rendered":"https:\/\/wpdev.acsu.buffalo.edu\/virtualglycome\/?page_id=37"},"modified":"2025-03-01T19:23:59","modified_gmt":"2025-03-01T19:23:59","slug":"gnat-glycosylation-network-analysis-toolbox","status":"publish","type":"page","link":"https:\/\/ubwp.buffalo.edu\/virtualglycome\/gnat-glycosylation-network-analysis-toolbox\/","title":{"rendered":"GNAT (Glycosylation Network Analysis Toolbox)"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\"><strong><mark class=\"has-inline-color has-accent-3-color\"><kbd>A MATLAB toolbox to create glycosylation reaction network models<\/kbd><\/mark><\/strong><\/h3>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:100%\">\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>References<\/strong><\/h2>\n\n\n\n<p><a href=\"https:\/\/doi.org\/10.1371\/journal.pone.0100939\">a)  <span style=\"text-decoration: underline\">Liu, G. Puri, A. Neelamegham, S. &#8220;Computational Framework for the Automated Construction of Glycosylation Reaction Networks&#8221;,<\/span><\/a> PloS one, 2014.<\/p>\n\n\n\n<p>b)  <a href=\"https:\/\/doi.org\/10.1371\/journal.pone.0100939\"><span style=\"text-decoration: underline\">Liu, G. Neelamegham, S.<\/span><\/a><a href=\"https:\/\/academic.oup.com\/bioinformatics\/article\/29\/3\/404\/257828\"><span style=\"text-decoration: underline\">&#8220;Glycosylation Network Analysis Toolbox: a MATLAB-based environment for systems glycobiology&nbsp;&#8221; Bioinformatics, 29:3, Pg 404\u2013406, 2013.<\/span><\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Introduction<\/strong><\/h2>\n<\/div>\n<\/div>\n\n\n\n<h3 class=\"wp-block-heading\">&nbsp; &nbsp; &nbsp;&nbsp;<strong>GNAT is a free open-source MATLAB toolbox<\/strong>. It is:<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Written using MATLAB and Java. &nbsp; &nbsp; &nbsp;<\/li>\n\n\n\n<li>Supported in Windows, Linux and Mac OS platforms.<\/li>\n\n\n\n<li>Available from&nbsp;<a href=\"http:\/\/sourceforge.net\/projects\/gnatmatlab\/files\/\" target=\"_blank\" rel=\"noreferrer noopener\"><span style=\"text-decoration: underline\">http:\/\/sourceforge.net\/projects\/gnatmatlab\/files\/<\/span>.<\/a><\/li>\n\n\n\n<li>Individual GNAT commands can be implemented from the MATLAB command prompt.&nbsp;<\/li>\n\n\n\n<li>Custom MATLAB .m scripts can be written to integrate GNAT functions and classes into other&nbsp;code. Toolbox Demos and the GettingStarted.pdf file enclosed with the toolbox provide sample scripts.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Feature&nbsp;<\/strong><\/h2>\n\n\n\n<p>GNAT contains a variety of classes to describe glycans and glycosylation reaction networks.&nbsp;It also provides various methods to manipulate these classes.The most recent release of&nbsp;&nbsp;GNAT (GNATv2beta.zip) provides a variety of functions that can be categorized in seven groups as below:&nbsp;<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Network Input\/Output<\/strong><\/h3>\n\n\n\n<p>These functions enable integration of XML (eXtensible Markup Language) based glycan&nbsp;structures into SBML (Systems Biology Markup Language) format files. These functions&nbsp;also allow reading &amp; writing of individual glycan and reaction network files.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Display Glycans, Enzymes and &nbsp;Networks&nbsp;<\/strong><\/h3>\n\n\n\n<p>functions enable visualization of individual glycans and glycosylation reaction&nbsp;networks in the MATLAB environment. Updated enzyme classes are now able to handle&nbsp;biochemical data on enzyme specificity including functional&nbsp;group,linkage and substrate specificity. These enzyme classes can&nbsp;also be displayed using GUI.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Database Query<\/strong><\/h3>\n\n\n\n<p>These functions enable linkage between GNAT and primarily two databases&nbsp;called GlycomeDB and the Consortium of Functional Glycomics (CFG).<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Network Inference<\/strong><\/h3>\n\n\n\n<p>These functions enable single-reaction inference and also automated full network&nbsp;reconstruction. The input for such algorithms include either sets of reactants&nbsp;and\/or products along with the list of enzymes present in a system.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Graph Operations<\/strong><\/h3>\n\n\n\n<p>These functions enable a variety of network manipulation methods. These include&nbsp;algorithms to find the path between any two glycans in the network, &nbsp;to generate&nbsp;the subset network model and to examine the network connectivity.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Mass Spectrometry Analysis<\/strong><\/h3>\n\n\n\n<p>Several functions are provided in order to enable the synthesis of reaction networks&nbsp;from mass spectrometry data.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Simulation<\/strong><\/h3>\n\n\n\n<p>These functions enable dynamic and steady-state simulation of reaction networks.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Installation <\/strong><\/h2>\n\n\n\n<p>A brief instruction for the installation of GNAT is provided as follows. &nbsp;Detailed&nbsp;step-by-step instructions are provided in the GettingStarted.pdf document enclosed&nbsp;in the package<strong>&nbsp;<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Start MATLAB. MATLAB version 7.13 (R2011b) or higher is recommended.&nbsp;<\/li>\n\n\n\n<li>Install libSBML5.6.0 or above in MATLAB environment (if not already installed).&nbsp;<\/li>\n\n\n\n<li>Install SBML toolbox 4.1.0 or above (if not already installed).&nbsp;<\/li>\n\n\n\n<li>Install GNAT in MATLAB. To do this, download the GNAT package and extract&nbsp;files into the installation directory (say: C:\\gnat). In the MATLAB command&nbsp;windows, go to this installation directory, and type &#8220;installGNAT&#8221;. This will&nbsp;install the software along with all necessary paths.&nbsp;<\/li>\n\n\n\n<li>Change java class path in MATLAB. To do this, open the &#8216;startup.m&#8217; file located in&nbsp;the toolbox\\startup folder. Edit &#8216;GNATInstallationDIR&#8217; (~10th line) to reflect the&nbsp;absolute directory path (e.g. &#8216;C:\\gnat&#8217;).Copy the &#8216;startup.m&#8217; file into the MATLAB&nbsp;startup folder.<\/li>\n<\/ul>\n\n\n\n<p><em><mark class=\"has-inline-color has-contrast-color\">Note<\/mark>: If the MATLAB path is set\/installed properly the first time, GNAT will be fully functional.&nbsp;If a &#8216;file cannot be found&#8217; error appears in subsequent MATLAB restarts,then the path set in the&nbsp;original installation was not saved when MATLAB was quit. One way to resolve this issue is to&nbsp;simply go to the GNAT installation directory and type &#8216;installGNAT&#8217; again. For more information&nbsp;about other hints, please see the &#8216;FAQ&#8217; section of the GettingStarted.pdf file.<\/em><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Usage guide<\/strong><\/h2>\n\n\n\n<p>\u00a0Detailed instructions for usage, examples and demos are provided in GettingStarted.pdf, available with the package.\u00a0<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Support<\/strong><\/h2>\n\n\n\n<p>For questions about the software usage, comments or&nbsp;suggestions&nbsp;please contact Sriram Neelamegham&nbsp;at&nbsp;<a href=\"mailto:neel@buffalo.edu\"><span style=\"text-decoration: underline\">neel@buffalo.edu<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A MATLAB toolbox to create glycosylation reaction network models References a) Liu, G. Puri, A. Neelamegham, S. &#8220;Computational Framework for the Automated Construction of Glycosylation Reaction Networks&#8221;, PloS one, 2014. 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