SAPH-ire TFx

A Machine Learning Recommendation Method and Webtool for the Prediction of Functional Post-Translational Modifications | ABSTRACT Post-translational Modifications (PTMs), chemical or proteinaceous covalent alterations to the side chains of amino acid residues in proteins, are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof and the lack of effective means for experimentalists to prioritize PTMs by functional significance, currently less than ~2% of all PTMs have an assigned biological function. Here, we describe a new artificial neural network model, SAPH-ire TFx for the functional prediction of experimentally observed eukaryotic PTMs. Unlike previous functional PTM prioritization models, SAPH-ire TFx is optimized with both receiver operating characteristic (ROC) and recall metrics that maximally capture the range of diverse feature sets comprising the functional modified eukaryotic proteome