This is an in-depth guide to the theory and practice of analyzing raw mass spectrometry (MS) data in proteomics. The volume outlines available bioinformatics programs, algorithms, and databases available for MS data analysis. General guidelines for data analysis using search engines such as Mascot, Xtandem, and VEMS are provided, with specific attention to identifying poor quality data and optimizing search parameters.

This volume discusses the latest mass spectrometry (MS)-based technologies for proteoform identification, characterization, and quantification. Some of the topics covered in this book include sample preparation, proteoform separation, proteoform gas-phase fragmentation, and bioinformatics tools for MS data analysis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Proteoform Identification: Methods and Protocols is a valuable resource for researchers in both academia and the biopharmaceutical industry who are interested in proteoform analysis using MS.

Proteomics is the study of the subsets of proteins present in different parts of an organism and how they change with time and varying conditions. Mass spectrometry is the leading technology used in proteomics, and the field relies heavily on bioinformatics to process and analyze the acquired data. Since recent years have seen tremendous developments in instrumentation and proteomics-related bioinformatics, there is clearly a need for a solid introduction to the crossroads where proteomics and bioinformatics meet. Computational Methods for Mass Spectrometry Proteomics describes the different instruments and methodologies used in proteomics in a unified manner. The authors put an emphasis on the computational methods for the different phases of a proteomics analysis, but the underlying principles in protein chemistry and instrument technology are also described. The book is illustrated by a number of figures and examples, and contains exercises for the reader. Written in an accessible yet rigorous style, it is a valuable reference for both informaticians and biologists. Computational Methods for Mass Spectrometry Proteomics is suited for advanced undergraduate and graduate students of bioinformatics and molecular biology with an interest in proteomics. It also provides a good introduction and reference source for researchers new to proteomics, and for people who come into more peripheral contact with the field.

With the development of new quantitative strategies and powerful bioinformatics tools to cope with the analysis of the large amounts of data generated in proteomics experiments, liquid chromatography with tandem mass spectrometry (LC-MS/MS) is making possible the analysis of proteins on a global scale, meaning that proteomics can now start competing with cDNA microarrays for the analysis of whole genomes. In LC-MS/MS in Proteomics: Methods and Applications, experts in the field provide protocols and up-to-date reviews of the applications of LC-MS/MS, with a particular focus on MS-based methods of protein and peptide quantification and the analysis of post-translational modifications. Beginning with overviews of the use of LC-M/MS in protein analysis, the book continues with topics such as protocols for the analysis of post-translational modifications, with particular focus on phosphorylation and glycosylation, popular techniques for quantitative proteomics, such as multiple reaction monitoring, metabolic labelling, and chemical tagging, biomarker discovery in biological fluids, as well as novel applications of LC-MS/MS. Written in the highly successful Methods in Molecular BiologyTM series format, chapters include introductions to their respective subjects, lists of necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, LC-MS/MS in Proteomics: Methods and Applications presents the techniques and concepts necessary in order to aid proteomic practitioners in the application of LC-MS/MS to essentially any biological problem.

The aim of the book is to give the reader a basic insight of Mass spectrometry-based bioinformatics. In the past, Bioinformatics has been mostly classified as a bridge discipline between Informatics and Biology rather than an independent scientific discipline. But with the comprehensive accumulation of biological data and the resulting challenges Bioinformaticians concentrate more on their own research rather than simply serving as technologists for others. Nowadays, the focus in Bioinformatics is mainly on the development of sophisticated algorithms capable of extracting useful knowledge from large data sets by combining methods from statistics and artificial intelligence. This beginners guide will help to illustrate some of the common algorithmic problems occurring in typical high throughput mass spectrometry protein identification experiments. A general introduction to Python programming language including standard programming techniques and their role in problem solving will be provided.

Introduction to Protein Mass Spectrometry provides a comprehensive overview of this increasingly important, yet complex, analytical technique. Unlike many other methods which automatically yield an absolutely unique protein name as output, protein mass spectrometry generally requires a deduction of protein identity from determination of peptide fragmentation products. This book enables readers to both understand, and appreciate, how determinations about protein identity from mass spectrometric data are made. Coverage begins with the technical basics, including preparations, instruments, and spectrometric analysis of peptides and proteins, before exploring applied use in biological applications, bioinformatics, database, and software resources. Citing the most recent and relevant work in the field of biological mass spectrometry, the book is written for researchers and scientists new to the field, but is also an ideal resource for those hoping to hone their analytical abilities. Offers introductory information for scientists and researchers new to the field, as well as advanced insight into the critical assessment of computer-analyzed mass spectrometric results and their current limitations Provides examples of commonly-used MS instruments from Bruker, Applied Biosystems, JEOL, Thermo Scientific/Thermo Fisher Scientific, IU, and Waters Includes biological applications and exploration of analytical tools and databases for bioinformatics

This thorough book collects methods and strategies to analyze proteomics data. It is intended to describe how data obtained by gel-based or gel-free proteomics approaches can be inspected, organized, and interpreted to extrapolate biological information. Organized into four sections, the volume explores strategies to analyze proteomics data obtained by gel-based approaches, different data analysis approaches for gel-free proteomics experiments, bioinformatic tools for the interpretation of proteomics data to obtain biological significant information, as well as methods to integrate proteomics data with other omics datasets including genomics, transcriptomics, metabolomics, and other types of data. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that will ensure high quality results in the lab. Authoritative and practical, Proteomics Data Analysis serves as an ideal guide to introduce researchers, both experienced and novice, to new tools and approaches for data analysis to encourage the further study of proteomics.

This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical proteomics or metabolomics, researchers will not only be confronted with new high dimensional data types—as opposed to the familiar data structures in more classical genomics—but also with great variation between distinct types of mass spectral measurements derived from different platforms, which may complicate analyses, comparison, and interpretation of results.

Second Edition provides up-to-the-minute discussions on the application of mass spectrometry to the biological sciences. Shows how and why experiments are performed and furnishes details to facilitate duplication of results.

To date, processing of high-throughput Mass Spectrometry (MS) data is accomplished using serial algorithms. Developing new methods to process MS data is an active area of research but there is no single strategy that focuses on scalability of MS based methods. Mass spectrometry is a diverse and versatile technology for high-throughput functional characterization of proteins, small molecules and metabolites in complex biological mixtures. In the recent years the technology has rapidly evolved and is now capable of generating increasingly large (multiple tera-bytes per experiment) and complex (multiple species/microbiome/high-dimensional) data sets. This rapid advance in MS instrumentation must be matched by equally fast and rapid evolution of scalable methods developed for analysis of these complex data sets. Ideally, the new methods should leverage the rich heterogeneous computational resources available in a ubiquitous fashion in the form of multicore, manycore, CPU-GPU, CPU-FPGA, and IntelPhi architectures. The absence of these high-performance computing algorithms now hinders scientific advancements for mass spectrometry research. In this book we illustrate the need for high-performance computing algorithms for MS based proteomics, and proteogenomics and showcase our progress in developing these high-performance algorithms.