Discovery of protein phosphorylation motifs through exploratory data analysis.

ABSTRACT:

Background

The need for efficient algorithms to uncover biologically relevant phosphorylation motifs has become very important with rapid expansion of the proteomic sequence database along with a plethora of new information on phosphorylation sites. Here we present a novel unsupervised method, called Motif Finder (in short, F-Motif) for identification of phosphorylation motifs. F-Motif uses clustering of sequence information represented by numerical features that exploit the statistical information hidden in some foreground data. Furthermore, these identified motifs are then filtered to find "actual" motifs with statistically significant motif scores.

Results and discussion

We have applied F-Motif to several new and existing data sets and compared its performance with two we

SUBMITTER: Chen YC 

PROVIDER: S-EPMC3102080 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature