/var/lib/mobyle/programs/netNglyc.xml

<?xml version='1.0' encoding='UTF-8'?>
<!-- XML Authors: Corinne Maufrais, Nicolas Joly and Bertrand Neron,             -->
<!-- 'Biological Software and Databases' Group, Institut Pasteur, Paris.         -->
<!-- Distributed under LGPLv2 License. Please refer to the COPYING.LIB document. -->
<program>
  <head>
    <name>netNglyc</name>
    <version>1.0c</version>
    <xi:include xmlns:xi="http://www.w3.org/2001/XInclude" href="Entities/cbs_package.xml"/>
    <doc>
      <title>netNglyc</title>
      <description>
        <text lang="en">predict N-glycosylation sites in proteins.</text>
      </description>
      <sourcelink>http://www.cbs.dtu.dk/cgi-bin/nph-sw_request?netNglyc</sourcelink>
      <authors>Ramneek Gupta, ramneek@cbs.dtu.dk</authors>
      <reference>Prediction of N-glycosylation sites in human proteins.
                 R. Gupta, E. Jung and S. Brunak.
                 In preparation, 2004.
      </reference>
      <doclink>http://www.cbs.dtu.dk/services/NetNGlyc/</doclink>
      <comment>
        <text lang="en">netNglyc predicts N-glycosylation sites in human proteins using artificial neural networks that examine the
       sequence context of Asn-Xaa-Ser/Thr sequons where Xaa  is  any  amino  acid  but  proline.</text>
      </comment>
    </doc>
    <category>sequence:protein:motifs</category>
    <category>sequence:protein:pattern</category>
    <category>sequence:protein:profiles</category>
  </head>
  <parameters>
     
    <parameter ishidden="1" iscommand="1">
      <name>netnglyc</name>
      <type>
        <datatype>
          <class>String</class>
        </datatype>
      </type>
      <format>
        <code proglang="perl">"netNglyc "</code>
        <code proglang="python">"netNglyc "</code>
      </format>
    </parameter>
   
    <parameter ismandatory="1" issimple="1" ismaininput="1">
      <name>sequence</name>
      <prompt lang="en">Input Sequence</prompt>
      <type>
        <datatype>
          <class>Sequence</class>
        </datatype>
        <dataFormat>FASTA</dataFormat>
      </type>
      <format>
        <code proglang="perl">" $value"</code>
        <code proglang="python">" " + str( value )</code>
      </format>
      <argpos>50</argpos>
     <example>
&gt;CBG_HUMAN
MPLLLYTCLLWLPTSGLWTVQAMDPNAAYVNMSNHHRGLASANVDFAFSLYKHLVALSPK
KNIFISPVSISMALAMLSLGTCGHTRAQLLQGLGFNLTERSETEIHQGFQHLHQLFAKSD
TSLEMTMGNALFLDGSLELLESFSADIKHYYESEVLAMNFQDWATASRQINSYVKNKTQG
KIVDLFSGLDSPAILVLVNYIFFKGTWTQPFDLASTREENFYVDETTVVKVPMMLQSSTI
SYLHDSELPCQLVQMNYVGNGTVFFILPDKGKMNTVIAALSRDTINRWSAGLTSSQVDLY
IPKVTISGVYDLGDVLEEMGIADLFTNQANFSRITQDAQLKSSKVVHKAVLQLNEEGVDT
AGSTGVTLNLTSKPIILRFNQPFIIMIFDHFTWSSLFLARVMNPV
     </example>
    </parameter>
    
    <parameter >
      <name>graphics</name>
      <prompt lang="en">generate graphics (-g).</prompt>
      <type>
        <datatype>
          <class>Boolean</class>
        </datatype>
      </type>
      <vdef>
        <value>0</value>
      </vdef>
      <format>
        <code proglang="perl">($value)? "-g " : ""</code>
        <code proglang="python">( "" , "-g " )[ bool( value ) ]</code>
      </format>
      <comment>
        <text lang="en">Generate  graphics,  plotting  the N-glycosylation potential and the thresh‐
              old(s) against the residue number of each predicted site. Two files will  be
              produced for each input sequence, one in PostScript and the other in GIF.</text>
      </comment>
      <argpos>10</argpos>
    </parameter>  

    <parameter>
      <name>threshold</name>
      <prompt lang="en">Show additional thresholds (0.32, 0.75, 0.90) in the graph(s).</prompt>
      <type>
        <datatype>
          <class>Boolean</class>
        </datatype>
      </type>
      <vdef>
        <value>0</value>
      </vdef>
      <format>
        <code proglang="perl">( defined $value )? "-a " : ""</code>
        <code proglang="python">( "" , "-a " )[ bool( value ) ]</code>
      </format>
      <comment>
        <text lang="en">Show  additional thresholds (0.32, 0.75 and 0.90) in the graphs. This option
              is ignored unless -g is also given.</text>
      </comment>
      <argpos>20</argpos>
    </parameter>
    
        <parameter>
      <name>aspargine</name>
      <prompt lang="en">Predict on all Asn residues (-f).</prompt>
      <type>
        <datatype>
          <class>Boolean</class>
        </datatype>
      </type>
      <vdef>
        <value>0</value>
      </vdef>
      <format>
        <code proglang="perl">( defined )? "-f " : ""</code>
        <code proglang="python">( "","-f ")[ bool( value ) ]</code>
      </format>
      <comment>
        <text lang="en">Predict on all asparagines in the input. Note that asparagines that  do  not
              occur  within the Asn-Xaa-Ser/Thr sequon are unlikely to be glycosylated, no
              matter what the prediction score.  The default is to  predict  only  on  the
              asparagines in the Asn-Xaa-Ser/Thr triplet.</text>
      </comment>
      <argpos>30</argpos>
    </parameter>

    <parameter isstdout="1">
      <name>results</name>
      <prompt lang="en">netNglyc report.</prompt>
      <type>
        <datatype>
          <superclass>Report</superclass>
          <class>NetNglyc</class>
        </datatype>
      </type>
      <filenames>
        <code proglang="perl">"netNglyc.out"</code>
        <code proglang="python">"netNglyc.out"</code>
      </filenames>
      <comment>
      <div xmlns="http://www.w3.org/1999/xhtml">
        <p> Each input sequence is displayed with  the  predicted  
        N-glycosylation sites highlighted. For each site the following is shown:</p>
        <ul>      
          <li>sequence name</li>
          <li>position in the sequence</li>
          <li>sequence motif</li>
          <li>N-glycosylation potential</li>
          <li>Jury agreement, 9 networks</li>
          <li>Prediction strength (+, ++ or +++)</li>
        </ul>
        </div>
      </comment>
    </parameter> 
    
    
    <parameter isout="1">
      <name>postscript</name>
      <prompt lang="en">graphic in PostScript</prompt>
      <type>
        <datatype>
          <superclass>Binary</superclass>
          <class>NetNGlyc_Graph</class>
        </datatype>
        <dataFormat>Postscript</dataFormat>
      </type>
      <precond>
        <code proglang="python">graphics</code>
      </precond>
      <filenames>
        <code proglang="perl">"*.ps"</code>
        <code proglang="python">"*.ps"</code>
      </filenames>
      <comment>
        <text lang="en"> plotting the N-glycosylation potential and the threshold(s) against the residue
              number of each predicted site.
        </text>
      </comment>
    </parameter> 
    
    <parameter isout="1">
      <name>gif</name>
      <prompt lang="en">graphic in GIF</prompt>
      <type>
        <datatype>
          <superclass>Binary</superclass>
          <class>NetNGlyc_Graph</class>
        </datatype>
        <dataFormat>GIF</dataFormat>
      </type>
      <precond>
       <code proglang="perl">$graphics</code>
        <code proglang="python">graphics</code>
      </precond>
      <filenames>
        <code proglang="perl">"*.gif"</code>
        <code proglang="python">"*.gif"</code>
      </filenames>
      <comment>
        <text lang="en"> plotting the N-glycosylation potential and the threshold(s) against the residue
              number of each predicted site.
        </text>
      </comment>
    </parameter> 
    
  </parameters>
</program>
mobyle-programs 5.1.2-1 / var / lib / mobyle / programs / netNglyc.xml
