Computational Methods for Predicting Post-Translational Modification Sites (Volume 2499)

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 Methods in Molecular Biology 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 protocols.

 Authoritative and cutting-edge, Authoritative and cutting-edge,  Computational Methods for Predicting Post-Translational Modification Sites aims to be a useful guide for researchers who are interested in the field of PTM site prediction. 

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 Methods in Molecular Biology 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 protocols.

 

Authoritative and cutting-edge, Authoritative and cutting-edge,  Computational Methods for Predicting Post-Translational Modification Sites aims to be a useful guide for researchers who are interested in the field of PTM site prediction.