title: Data Analysis Strategies for Protein Modification Identification.
abstract: Mass spectrometry-based proteomics provides a powerful tool for large-scale analysis of protein modifications. Statistical and computational analysis of mass spectrometry data is a key step in protein modification identification. This chapter presents common and advanced data analysis strategies for modification identification, including variable modification search, unrestrictive approaches for modification discovery, false discovery rate estimation and control methods, and tools for modification site localization.
authors.affiliation: National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Zhongguancun East Road 55, Beijing, 100190, China. yfu@amss.ac.cn.
authors.forename: Yan
authors.initials: Y
authors.lastname: Fu
mesh_terms: D019295:Computational Biology / Q000379:methods* / Q000592:standards; D030562:Databases, Protein; D011499:Protein Processing, Post-Translational; D040901:Proteomics / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results; D057386:Search Engine; D064878:Web Browser
keywords: False discovery rate; Modification discovery; Modification localization; Protein modification s; Variable modification search