Abstract
Posttranslational modifications (PTMs), which are processes of adding covalent groups in protein amino acids after the translation, play an important role in regulating proteins' localization, degradation, and functions. Different PTMs both within a single protein and across multiple proteins can work together or regulate reciprocally, known as PTM cross talk. However, high-throughput experimental identifications of PTM cross talk are lack due to technical limitations. In this chapter, we review in silico prediction approaches and illustrate the usage of PTM-X, a suite of recently proposed machine learning methods to predict both intra- and interprotein PTM cross talk.
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