</head>
<body>
<strong>JNet Secondary Structure Prediction</strong>
-<p>Secondary structure prediction methods attempts to infer the
-likely secondary structure for a protein based on its amino acid
-composition and similarity to sequences with known secondary structure.
-The JNet method uses several different neural networks and decides on
-the most likely prediction via a jury network. <br>
-<ul>
+<p>
+ Secondary structure prediction methods attempts to infer the likely
+ secondary structure for a protein based on its amino acid
+ composition and similarity to sequences with known secondary
+ structure. The most recent version of the method, JPred4, employs a
+ series of neural networks trained to predict different secondary
+ structure types from a sequence profile, and when necessary, employs
+ a jury network to identify the most likely secondary structure
+ prediction.<br><ul><li>Drozdetskiy A, Cole C, Procter J & Barton GJ. (2015)<br/>
+JPred4: a protein secondary structure prediction server<br/>
+<em>Nucleic Acids Research</em>, <strong>Web Server issue</strong> (first published 15th April 2015)<br/>
+<a href="http://dx.doi.org/10.1093/nar/gkv332">http://dx.doi.org/10.1093/nar/gkv332</a>
+ </li>
<li>Cole C., Barber J.D. and Barton G.J. (2008) The Jpred 3
secondary structure prediction server <em>Nucleic Acids Research</em> <strong>36</strong>
W197-W201</li>
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