NetPhosYeast: prediction of protein phosphorylation sites in yeast

C.R. Ingrell, Martin Lee Miller, O.N. Jensen, Nikolaj Blom

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast-an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation sites compared to those in humans, suggesting the need for an yeast-specific phosphorylation site predictor. NetPhosYeast achieves a correlation coefficient close to 0.75 with a sensitivity of 0.84 and specificity of 0.90 and outperforms existing predictors in the identification of phosphorylation sites in yeast.
    Original languageEnglish
    JournalBioinformatics
    Volume23
    Issue number7
    Pages (from-to)895-897
    ISSN1367-4803
    DOIs
    Publication statusPublished - 2007

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