Table 1.
Computational prediction of S-nitrosylation sites from experimentally identified S-nitrosylated proteins in plants using GPS-SNO 1.0, iSNO-PseAAC, iSNO-AAPair, and SNOSite software.
Table 2.
Prediction of Arabidopsis candidate proteins for S-nitrosylation using the GPS-SNO 1.0 software.
Table 3.
Subcellular compartment classification of Arabidopsis proteins.
Figure 1.
Functional distribution of predicted candidate proteins for S-nitrosylation has been determined using the MapMan Ontology tool (http://mapman.gabipd.org/).
Others; include all functional classes which have less than 5% of predicted candidates.
Figure 2.
Percentage of candidate proteins for S-nitrosylation in different functional categories.
Functional assignment has been done using the MapMan Ontology tool (http://mapman.gabipd.org/web/guest/mapman).
Table 4.
Percentage of predicted candidate proteins for S-nitrosylation in signaling subclasses.
Table 5.
Prediction of S-nitrosylated sites from experimentally identified S-nitrosylated proteins by GPS-SNO software.
Table 6.
Computational analysis of proteins, which S-nitrosylation sites were identified by BS-ICAT technology [28].