From: MetaDisorder: a meta-server for the prediction of intrinsic disorder in proteins
Method | Short description | Availability | Ref. |
---|---|---|---|
DisEMBL | ANN trained to predict classic loops (DSSP), flexible loops with high B-factors, missing coordinates in X-ray structures, regions of low-complexity and prone to aggregation. | local installation | [21] |
DISOPRED2 | SVM trained to predict residues with missing coordinates. | local installation | [22] |
DISpro | Recursive neural networks (RNNs) trained to predict missing coordinates. | local installation | [23] |
GlobPlot | A simple method based on several hydrophobicity scales to predict regions of missing coordinates and loops with high B-factors. | local installation | [24] |
iPDA | Incorporates information about sequence conservation, predicted secondary structure, sequence complexity and hydrophobic clusters. | web service | [25] |
IUPred | Estimates pairwise interaction energies using a statistical potential. Two versions for predicting long and short disorder. | web service | [26] |
Pdisorder | Combination of neural network, linear discriminant function and acute smoothing procedure is used for recognition of disordered and ordered regions in proteins. | web service | [27] |
Poodle-s | SVM trained for short disorder detection (uses PSSMs generated by PSI-BLAST). | web service | [28] |
Poodle-l | Predicts long disorder using an SVM. | web service | [29] |
PrDOS | Predicts missing coordinates in 3D structure using SVM and PSSMs from PSI-BLAST. | web service | [30] |
Spritz | Predicts long and short disorder (missing coordinates) using two separate SVMs. Utilizes secondary structure. | web service | [31] |
RONN | Predicts missing coordinates using an ANN. | local installation | [33] |