Computational Methods for Predicting Post-Translational Modification Sites (Methods in Molecular Biology 2499)
Computational Methods for Predicting Post-Translational Modification Sites is an essential volume in the renowned Methods in Molecular Biology series, dedicated to guiding researchers through the latest computational approaches for identifying and analyzing post-translational modifications (PTMs) in proteins. PTMs, such as phosphorylation, ubiquitination, methylation, and glycosylation, play a vital role in regulating protein function, signaling pathways, and cellular processes, making their accurate prediction critical in both basic and applied biological research.
This expertly curated book combines theoretical foundations with practical step-by-step tutorials, enabling readers to master state-of-the-art computational pipelines and machine learning algorithms for PTM site prediction. Each chapter is written by experienced scientists and follows the trusted Methods in Molecular Biology format—offering an introduction to the subject, a detailed list of software, datasets, and system requirements, followed by easy-to-follow protocols and troubleshooting tips to ensure reproducible results.
Key Features of “Computational Methods for Predicting Post-Translational Modification Sites”:
-
Comprehensive PTM Coverage: Includes protocols for predicting diverse PTM types across various species.
-
Bioinformatics Tools: Guidance on using established prediction servers, software packages, and databases.
-
Machine Learning Approaches: Implementation of AI-based models for improved prediction accuracy.
-
Data Preparation & Validation: Methods for curating datasets, cross-validation, and performance assessment.
-
Integration with Experimental Methods: Strategies for combining computational predictions with laboratory validation.
-
Troubleshooting Support: Expert tips to overcome common challenges in computational PTM analysis.
Ideal for bioinformaticians, computational biologists, proteomics researchers, molecular biologists, and systems biologists, this volume provides both newcomers and experienced professionals with the knowledge and tools to accelerate PTM research. From understanding the biochemical significance of PTMs to implementing custom predictive models, readers will find practical guidance for every step of the process.
