Highly specific prediction of phosphorylation sites in proteins.
CONCLUSIONS
The prediction of significant short functional protein sequences has inherent problems. In predicting phosphorylation sites, problems came from the shortness of phosphorylation sites, the difficulties in maintaining many different predefined models of binding sites, and the difficulties of obtaining highly sensitive predictions and of obtaining predictions with a constant sensitivity and specificity. The algorithm presented in this paper overcomes these problems. The proposed algorithm PHOSITE is based on the case-based sequence analysis. This enables the prediction of phosphorylation sites with constant specificity and sensitivity. Furthermore, this method leads not only to the prediction of phosphorylation sites in general but also predicts the most probable type of kinase involved.


BACKGROUND
The tool PHOSITE implementing the presented method can be evaluated under the website http://www.phosite.com.
CeVis, University of Bremen, Universitaetsallee 29, 28359 Bremen, Germany. koenig@cevis.uni-bremen.de <koenig@cevis.uni-bremen.de>
Matthias
M
Koenig
Niels
N
Grabe
D000465:Algorithms; D001665:Binding Sites; D017553:Phosphorus Compounds / Q000737:chemistry* / Q000378:metabolism; D010766:Phosphorylation; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D016415:Sequence Alignment / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
D017553:Phosphorus Compounds; D011506:Proteins