X-Git-Url: http://source.jalview.org/gitweb/?a=blobdiff_plain;f=help%2Fhtml%2FwebServices%2FproteinDisorder.html;h=1c35bf3ca3c252916581e668906d02e79a1d90e4;hb=dde303bc73617ab4eb3e681e67cf899e6a971318;hp=2c981397cc22cdfe51bf327deaae839b562661ef;hpb=528c0f1815bc67b54618ad5b16c2162946974caf;p=jalview.git diff --git a/help/html/webServices/proteinDisorder.html b/help/html/webServices/proteinDisorder.html index 2c98139..1c35bf3 100644 --- a/help/html/webServices/proteinDisorder.html +++ b/help/html/webServices/proteinDisorder.html @@ -28,26 +28,25 @@ The Web Services→Disorder menu in the alignment window allows access to protein disorder prediction services provided by the configured JABAWS servers. Each service operates on sequences in the - alignment or currently selected region (since Jalview - 2.8.0b1) to identify regions likely to be unstructured or - flexible, or alternately, fold to form globular domains. + href="http://www.compbio.dundee.ac.uk/jabaws">JABAWS + servers. Each service operates on sequences in the alignment or + currently selected region (since Jalview 2.8.0b1) to + identify regions likely to be unstructured or flexible, or + alternately, fold to form globular domains.

Predictor results include both sequence features and sequence associated alignment annotation rows. Features display is controlled from - the Feature Settings + href="../features/seqfeatures.html">sequence features and + sequence associated alignment + annotation rows. Features display is controlled from the Feature Settings dialog box. Clicking on the ID for a disorder prediction annotation row will highlight or select (if double clicked) the associated sequence for that row. You can also use the Sequence Associated option in the Colour By Annotation dialog box to colour sequences according to - the results of predictors shown as annotation rows. + href="../colourSchemes/annotationColouring.html">Colour + By Annotation dialog box to colour sequences according to the + results of predictors shown as annotation rows.

JABAWS 2.0 provides four disorder predictors which are described below:

@@ -74,10 +73,10 @@ Sequence Feature &
Annotation Row Predicts loops/coils according to DSSP definition[1].
Features mark range(s) of residues predicted as - loops/coils, and annotation row gives raw value for each - residue. Value over 0.516 indicates loop/coil. + href="#dsspstates">[1].
Features mark range(s) + of residues predicted as loops/coils, and annotation row gives + raw value for each residue. Value over 0.516 indicates + loop/coil. @@ -117,13 +116,13 @@

RONN a.k.a. Regional Order Neural Network
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. + href="http://www.strubi.ox.ac.uk/RONN">RONN a.k.a. + Regional Order Neural Network
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.

@@ -147,14 +146,13 @@

IUPred
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. + href="http://iupred.enzim.hu/Help.php">IUPred
+ 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.

@@ -196,17 +194,16 @@

GLOBPLOT
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.
+ href="http://globplot.embl.de/">GLOBPLOT
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.
Name