Welcome to the SAskatchewan PHosphorylation Internet REsource (SAPHIRE). Hosted by the University of Saskatchewan, this site currently contains three tools designed for the in silico analysis of phosphorylation sites.

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This is the new version of SAPHIRE, using the Ubuntu VM.

Tool #1: PHOSFER

PHOSFER uses a novel machine-learning approach in order to predict phosphorylation sites in soybean proteins, and will be expanded to predict for other plants in the future.

If you use PHOSFER, please cite:
B. Trost and A. Kusalik. Computational phosphorylation site prediction in plants using random forests and organism-specific instance weights. Bioinformatics 29(6):686-694, 2013.

Tool #2: DAPPLE 2

DAPPLE 2 is a homology-based method for predicting post-translational modification sites in an organism of interest. 20 different types of PTMs are supported, including phosphorylation, acetylation, ubiquitination, methylation, and glycosylation. It uses BLAST searches of experimentally-determined PTM sites in one organism (or several organisms) to predict PTM sites in an organism of interest. It outputs a table containing information helpful for choosing PTM sites that are of interest to you, such as the number of sequence differences between the query site and the hit site, the location of the query site and the hit site in their respective intact proteins, and whether the corresponding intact proteins are reciprocal BLAST hits (and thus predicted orthologues).

The original version of DAPPLE, which supported only phosphorylation, is described in the following paper:
B. Trost, R. Arsenault, P. Griebel, S. Napper, and A. Kusalik. DAPPLE: a pipeline for the homology-based prediction of phosphorylation sites. Bioinformatics 29(13):1693-1695, 2013.

DAPPLE 2 is described in the following paper:
B. Trost, F. Maleki, A. Kusalik, and S. Napper. DAPPLE 2: a tool for the homology-based prediction of post-translational modification sites. Journal of Proteome Research 15(8):2760-2767, 2016.

Tool #3: PIIKA 2.5

PIIKA 2.5 is a tool for analyzing data originating from kinome microarrays.

The original version of PIIKA is described in the following paper:
Y. Li, R. J. Arsenault, B. Trost, J. Slind, P. J. Griebel, S. Napper, and A. Kusalik. A systematic approach for analysis of peptide array kinome data. Science Signaling 5(220):pl2, 2012.

PIIKA 2 includes many new features and also has a web-based interface. It is described in the following paper:
B. Trost, J. Kindrachuk, P. Määttänen, S. Napper, and A. Kusalik. PIIKA 2: An Expanded, Web-Based Platform for Analysis of Kinome Microarray Data. PLOS ONE 8(11):e80837, 2013.

To use PIIKA 2 (old version), go here: PIIKA 2




Image credits: Sierra Blakely (PHOSFER) and Flickr users Soggydan (DAPPLE) and wildxplorer (PIIKA 2).