- <p>
- <strong><a name="ronn"></a><a
- href="http://www.strubi.ox.ac.uk/RONN">RONN</a></strong> <em>a.k.a.</em>
- Regional Order Neural Network<br />This predictor employs an approach
- known as the 'bio-basis' method to predict regions of disorder in
- sequences based on their local similarity with a gold-standard set of
- disordered protein sequences. It yields a set of disorder prediction
- scores, which are shown as sequence annotation below the alignment.
- </p>
- <table border="1">
- <tr>
- <td><strong>Name</strong></td>
- <td><strong>Annotation type</strong></td>
- <td><strong>Description</strong></td>
- </tr>
- <tr>
- <td><strong>JRonn</strong>[2]</td>
- <td>Annotation Row</td>
- <td>RONN score for each residue in the sequence. Scores above
- 0.5 identify regions of the protein likely to be disordered.</td>
- </tr>
- </table>
- <p>
- <em>[2]. JRonn denotes the score for this server because JABAWS
- runs a Java port of RONN developed by Peter Troshin and distributed
- as part of <a href="http://www.biojava.org/">Biojava 3</a>
- </em>
- </p>
- <p>
- <strong><a name="iupred"></a><a
- href="http://iupred.enzim.hu/Help.php">IUPred</a></strong><br /> IUPred
- employs an empirical model to estimate likely regions of disorder.
- There are three different prediction types offered, each using
- different parameters optimized for slightly different applications. It
- provides raw scores based on two models for predicting regions of
- 'long disorder' and 'short disorder'. A third predictor identifies
- regions likely to form structured domains.
- </p>
- <table border="1">
- <tr>
- <td><strong>Name</strong></td>
- <td><strong>Annotation type</strong></td>
- <td><strong>Description</strong></td>
- </tr>
- <tr>
- <td><strong>Long disorder</strong></td>
- <td>Annotation Row</td>
- <td>Prediction of context-independent global disorder that
- encompasses at least 30 consecutive residues of predicted disorder.
- Employs a 100 residue window for calculation.<br />Values above 0.5
- indicates the residue is intrinsically disordered.
- </td>
- </tr>
- <tr>
- <td><strong>Short disorder</strong></td>
- <td>Annotation Row</td>
- <td>Predictor for short, (and probably) context-dependent,
- disordered regions, such as missing residues in the X-ray structure
- of an otherwise globular protein. Employs a 25 residue window for
- calculation, and includes adjustment parameter for chain termini
- which favors disorder prediction at the ends.<br />Values above 0.5
- indicate short-range disorder.
- </td>
- </tr>
- <tr>
- <td><strong>Structured domains</strong></td>
- <td>Sequence Feature</td>
- <td>Features highlighting likely globular domains useful for
- structure genomics investigation. <br />Post-analysis of disordered
- region profile to find continuous regions confidently predicted to
- be ordered. Neighbouring regions close to each other are merged,
- while regions shorter than the minimal domain size of at least 30
- residues are ignored.
- </td>
- </tr>
- </table>
- <p>
- <strong><a name="globplot"></a><a
- href="http://globplot.embl.de/">GLOBPLOT</a></strong><br /> Defines regions
- of globularity or natively unstructured regions based on a running sum
- of the propensity of residues to be structured or unstructured. The
- propensity is calculated based on the probability of each amino acid
- being observed within well defined regions of secondary structure or
- within regions of random coil. The initial signal is smoothed with a
- Savitzky-Golay filter, and its first order derivative computed.
- Residues for which the first order derivative is positive are
- designated as natively unstructured, whereas those with negative
- values are structured.<br />
- <table border="1">
- <tr>
- <td><strong>Name</strong></td>
- <td><strong>Annotation type</strong></td>
- <td><strong>Description</strong></td>
- </tr>
- <tr>
- <td><strong>Disordered Region</strong></td>
- <td>Sequence Feature</td>
- <td><br />Sequence features marking range(s) of residues with
- positive dydx values (correspond to the #Disorder column from JABAWS
- results)</td>
- </tr>
- <tr>
- <td><strong>Globular Domain</strong>
- <td>Sequence Feature</td>
- <td>Putative globular domains</td>
- </tr>
- <tr>
- <td><strong>Dydx</strong></td>
- <td>Annotation row</td>
- <td>First order derivative of smoothed score. Values above 0
- indicates residue is disordered.</td>
- </tr>
- <tr>
- <td><strong>Smoothed Score<br />Raw Score
- </strong></td>
- <td>Annotation Row</td>
- <td>The smoothed and raw scores used to create the differential
- signal that indicates the presence of unstructured regions.<br /> <em>These
- are hidden by default, but can be shown by right-clicking on the
- alignment annotation panel and selecting <strong>Show
- hidden annotation</strong>
- </em>
- </td>
- </tr>
- </table>
- <p>
- <em>Documentation and thresholds for the JABAWS Disorder
- predictors adapted from a personal communication by Nancy Giang,
- 2012.</em>
- </p>
+ <p>
+ <strong><a name="ronn"></a><a
+ href="http://www.strubi.ox.ac.uk/RONN">RONN</a></strong> <em>a.k.a.</em>
+ Regional Order Neural Network<br />This predictor employs an
+ approach known as the 'bio-basis' method to predict regions of
+ disorder in sequences based on their local similarity with a
+ gold-standard set of disordered protein sequences. It yields a set
+ of disorder prediction scores, which are shown as sequence
+ annotation below the alignment.
+ </p>
+ <table border="1">
+ <tr>
+ <td><strong>Name</strong></td>
+ <td><strong>Annotation type</strong></td>
+ <td><strong>Description</strong></td>
+ </tr>
+ <tr>
+ <td><strong>JRonn</strong>[2]</td>
+ <td>Annotation Row</td>
+ <td>RONN score for each residue in the sequence. Scores above
+ 0.5 identify regions of the protein likely to be disordered.</td>
+ </tr>
+ </table>
+ <p>
+ <em>[2]. JRonn denotes the score for this server because JABAWS
+ runs a Java port of RONN developed by Peter Troshin and
+ distributed as part of <a href="http://www.biojava.org/">Biojava
+ 3</a>
+ </em>
+ </p>
+ <p>
+ <strong><a name="iupred"></a><a
+ href="http://iupred.enzim.hu/">IUPred</a></strong><br />
+ IUPred employs an empirical model to estimate likely regions of
+ disorder. There are three different prediction types offered, each
+ using different parameters optimized for slightly different
+ applications. It provides raw scores based on two models for
+ predicting regions of 'long disorder' and 'short disorder'. A third
+ predictor identifies regions likely to form structured domains.
+ </p>
+ <table border="1">
+ <tr>
+ <td><strong>Name</strong></td>
+ <td><strong>Annotation type</strong></td>
+ <td><strong>Description</strong></td>
+ </tr>
+ <tr>
+ <td><strong>Long disorder</strong></td>
+ <td>Annotation Row</td>
+ <td>Prediction of context-independent global disorder that
+ encompasses at least 30 consecutive residues of predicted
+ disorder. Employs a 100 residue window for calculation.<br />Values
+ above 0.5 indicates the residue is intrinsically disordered.
+ </td>
+ </tr>
+ <tr>
+ <td><strong>Short disorder</strong></td>
+ <td>Annotation Row</td>
+ <td>Predictor for short, (and probably) context-dependent,
+ disordered regions, such as missing residues in the X-ray
+ structure of an otherwise globular protein. Employs a 25 residue
+ window for calculation, and includes adjustment parameter for
+ chain termini which favors disorder prediction at the ends.<br />Values
+ above 0.5 indicate short-range disorder.
+ </td>
+ </tr>
+ <tr>
+ <td><strong>Structured domains</strong></td>
+ <td>Sequence Feature</td>
+ <td>Features highlighting likely globular domains useful for
+ structure genomics investigation. <br />Post-analysis of
+ disordered region profile to find continuous regions confidently
+ predicted to be ordered. Neighbouring regions close to each
+ other are merged, while regions shorter than the minimal domain
+ size of at least 30 residues are ignored.
+ </td>
+ </tr>
+ </table>
+ <p>
+ <strong><a name="globplot"></a><a
+ href="http://globplot.embl.de/">GLOBPLOT</a></strong><br /> Defines
+ regions of globularity or natively unstructured regions based on a
+ running sum of the propensity of residues to be structured or
+ unstructured. The propensity is calculated based on the probability
+ of each amino acid being observed within well defined regions of
+ secondary structure or within regions of random coil. The initial
+ signal is smoothed with a Savitzky-Golay filter, and its first order
+ derivative computed. Residues for which the first order derivative
+ is positive are designated as natively unstructured, whereas those
+ with negative values are structured.<br />
+ <table border="1">
+ <tr>
+ <td><strong>Name</strong></td>
+ <td><strong>Annotation type</strong></td>
+ <td><strong>Description</strong></td>
+ </tr>
+ <tr>
+ <td><strong>Disordered Region</strong></td>
+ <td>Sequence Feature</td>
+ <td><br />Sequence features marking range(s) of residues
+ with positive dydx values (correspond to the #Disorder column
+ from JABAWS results)</td>
+ </tr>
+ <tr>
+ <td><strong>Globular Domain</strong>
+ <td>Sequence Feature</td>
+ <td>Putative globular domains</td>
+ </tr>
+ <tr>
+ <td><strong>Dydx</strong></td>
+ <td>Annotation row</td>
+ <td>First order derivative of smoothed score. Values above 0
+ indicates residue is disordered.</td>
+ </tr>
+ <tr>
+ <td><strong>Smoothed Score<br />Raw Score
+ </strong></td>
+ <td>Annotation Row</td>
+ <td>The smoothed and raw scores used to create the
+ differential signal that indicates the presence of unstructured
+ regions.<br /> <em>These are hidden by default, but can be
+ shown by right-clicking on the alignment annotation panel and
+ selecting <strong>Show hidden annotation</strong>
+ </em>
+ </td>
+ </tr>
+ </table>
+ <p>
+ <em>Documentation and thresholds for the JABAWS Disorder
+ predictors adapted from a personal communication by Nancy Giang,
+ 2012.</em>
+ </p>