This volume describes computational approaches to predict multitudes of PTM sites. Chapters describe in depth approaches on algorithms, state-of-the-art Deep Learning based approaches, hand-crafted features, physico-chemical based features, issues related to obtaining negative training, sequence-based features, and structure-based features. Written in the format of the highly successful series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible prools.