title: Mining Conditional Phosphorylation Motifs.
abstract: Phosphorylation motifs represent position-specific amino acid patterns around the phosphorylation sites in the set of phosphopeptides. Several algorithms have been proposed to uncover phosphorylation motifs, whereas the problem of efficiently discovering a set of significant motifs with sufficiently high coverage and non-redundancy still remains unsolved. Here we present a novel notion called conditional phosphorylation motifs. Through this new concept, the motifs whose over-expressiveness mainly benefits from its constituting parts can be filtered out effectively. To discover conditional phosphorylation motifs, we propose an algorithm called C-Motif for a non-redundant identification of significant phosphorylation motifs. C-Motif is implemented under the Apriori framework, and it tests the statistical significance together with the frequency of candidate motifs in a single stage. Experiments demonstrate that C-Motif outperforms some current algorithms such as MMFPh and Motif-All in terms of coverage and non-redundancy of the results and efficiency of the execution. The source code of C-Motif is available at: https://sourceforge. net/projects/cmotif/.
authors.forename: Xiaoqing
authors.initials: X
authors.lastname: Liu
authors.forename: Jun
authors.initials: J
authors.lastname: Wu
authors.forename: Haipeng
authors.initials: H
authors.lastname: Gong
authors.forename: Shengchun
authors.initials: S
authors.lastname: Deng
authors.forename: Zengyou
authors.initials: Z
authors.lastname: He
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D010363:Pattern Recognition, Automated; D010748:Phosphopeptides / Q000737:chemistry*; D010766:Phosphorylation; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D010748:Phosphopeptides