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Figure 1 | BMC Bioinformatics

Figure 1

From: PostMod: sequence based prediction of kinase-specific phosphorylation sites with indirect relationship

Figure 1

Illustration of the noise-reducing system. Illustration of the noise-reducing system. In step 1, we find the top 5 hits for a given query, where P j is a phosphorylation peptide and N j is a non-phosphorylation peptide. Next, S combined scores are calculated between the top 5 hits and all peptides in a reference set (10 peptides), where if a peptide i is not included in top 5 hits for a peptide j the score (j, i) is set to zero. In step 3, by summing each row of indirect relationship matrix we calculate indirect scores. During summation we assume that scores between positive (or negative) peptides are signal, while those between positive (or negative) and negative (or positive) are noise. Finally, we check the number of phosphorylation peptides among the top 4 hits by indirect scores. In this example P2, P3, P4, and N2 are recognized as the top 4 hits, and among them 3 peptides are phosphorylation peptides, and thereby we predict that the query peptide is a phosphorylation peptide.

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