Daniel C. Liebler masterfully introduces the science of proteomics by spelling out the basics of how one analyzes proteins and proteomes, and just how these approaches are then employed to investigate their roles in living systems. He explains the key concepts of proteomics, how the analytical instrumentation works, what data mining and other software tools do, and how these tools can be integrated to study proteomes. Also discussed are how protein and peptide separation techniques are applied in proteomics, how mass spectrometry is used to identify proteins, and how data analysis software enables protein identification and the mapping of modifications. In addition, there are proteomic approaches for analyzing differential protein expression, characterizing proteomic diversity, and dissecting protein-protein interactions and networks.
Introducing Proteomics gives a concise and coherent overview of every aspect of current proteomics technology, which is a rapidly developing field that is having a major impact within the life and medical sciences. This student-friendly book, based on a successful course developed by the author, provides its readers with sufficient theoretical background to be able to plan, prepare, and analyze a proteomics study. The text covers the following: Separation Technologies Analysis of Peptides/Proteins by Mass Spectrometry Strategies in Proteomics This contemporary text also includes numerous examples and explanations for why particular strategies are better than others for certain applications. In addition, Introducing Proteomics includes extensive references and a list of relevant proteomics information sources; essential for any student. This no-nonsense approach to the subject tells students exactly what they need to know, leaving out unnecessary information. The student companion site enhances learning and provides answers to the end of chapter problems. "I think this book will be a popular and valuable resource for students and newcomers to the field who would like to have an overview and initial understanding of what proteomics is about. The contents are well organized and address the major issues." —Professor Walter Kolch, Director, Systems Biology Ireland & Conway Institute, University College Dublin Companion Website www.wiley.com/go/lovric
Proteomics provides an introductory insight on proteomics, discussing the basic principles of the field, how to apply specific technologies and instrumentation, and example applications in human health and diseases. With helpful study questions, this textbook presents an easy to grasp and solid overview and understanding of the principles, guidelines, and especially the complex instrumentation operations in proteomics for new students and research scientists. Written by a leader in proteomics studies, Proteomics offers an expert perspective on the field and the future of proteomics.
Introduction to Computational Proteomics introduces the field of computational biology through a focused approach that tackles the different steps and problems involved with protein analysis, classification, and meta-organization. The book starts with the analysis of individual entities and works its way through the analysis of more complex entitie
Illustrates the Complex Biochemical Relations that Permit Life to ExistIt can be argued that the dawn of the 21st century has emerged as the age focused on molecular biology, which includes all the regulatory mechanisms that make cellular biochemical reaction pathways stable and life possible. For biomedical engineers, this concept is essential to
Introduction to Proteomics is written by seasoned researchers with years of practical experience. In addition to comprehensive discussions of the basic concepts, techniques, and applications of the subject, the text also includes an extensive glossary and a chapter containing laboratory exercises and protocols. While mass spectrometry is central to proteomics, the book discusses all of the analytical techniques a student is likely to need when faced with real-world problems, such as sample preparation, chromatographic and electrophoretic separation, micro-total analysis systems, and bioinformatics.
In this, the post-genomic age, our knowledge of biological systems continues to expand and progress. As the research becomes more focused, so too does the data. Genomic research progresses to proteomics and brings us to a deeper understanding of the behavior and function of protein clusters. And now proteomics gives way to neuroproteomics as we beg
Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution. The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis and modeling. This new standard effectively eliminates the differing methodologies used in studies and creates a unified approach. Readers will learn the advantages and disadvantages of the various techniques discussed, as well as potential difficulties inherent to all steps in the biomarker discovery process. A vital resource for biochemists, biologists, analytical chemists, bioanalytical chemists, clinical and medical technicians, researchers in pharmaceuticals, and graduate students, Proteomic and Metabolomic Approaches to Biomarker Discovery provides the information needed to reduce clinical error in the execution of research. - Describes the use of biomarkers to reduce clinical errors in research - Includes techniques from a range of biomarker discoveries - Covers all steps involved in biomarker discovery, from study design to study execution
Principles of Proteomics is designed specifically to explain the different stages of proteomic analysis, their complexities and their jargon to students and researchers in a non-technical overview of the field. The author describes the broad range of problems which proteomics can address, including structural proteomics, interaction proteomics, protein modification analysis and functional proteomics. Methodologies are described in user-friendly language, from the more traditional two-dimensional gel electrophoresis to the new developments in protein chip technologies. These are well presented in the context of overall strategies which can be adopted to address the different aspects of large-scale protein analysis.
Since the publishing of the first edition, the methodologies and instrumentation involved in the field of mass spectrometry-based proteomics has improved considerably. Fully revised and expanded, Mass Spectrometry Data Analysis in Proteomics, Second Edition presents expert chapters on specific MS-based methods or data analysis strategies in proteomics. The volume covers data analysis topics relevant for quantitative proteomics, post translational modification, HX-MS, glycomics, and data exchange standards, among other topics. Written in the highly successful Methods in Molecular Biology series format, chapters include brief introductions to their respective subjects, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Updated and authoritative, Mass Spectrometry Data Analysis in Proteomics, Second Edition serves as a detailed guide for all researchers seeking to further our knowledge in the field of proteomics.
