The handling and analysis of data generated by proteomics investigations represent a challenge for computer scientists, biostatisticians, and biologists to develop tools for storing, retrieving, visualizing, and analyzing genomic data. Informatics in Proteomics examines the ongoing advances in the application of bioinformatics to proteomics research and analysis. Through computer simulations, scientists can determine more about how diseases affect cells, predict how various drug interventions would work, and ultimately use proteins as therapeutic targets. This book first addresses the infrastructure needed for public protein databases. It discusses information management systems and user interfaces for storage, retrieval, and visualization of the data as well as issues surrounding data standardization and integration of protein sequences recorded in the last two decades. The authors subsequently examine the application of statistical and bioinformatic tools to data analysis, data presentation, and data mining. They discuss the implementation of algorithms, statistical methods, and computer applications that facilitate pattern recognition and biomarker discovery by integrating data from multiple sources. This book offers a well-rounded resource of informatic approaches to data storage, retrieval, and protein analysis as well as application-specific bioinformatic tools that can be used in disease detection, diagnosis, and treatment. Informatics in Proteomics captures the current state-of-the-art and provides a valuable foundation for future directions.

Bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, Proteome Informatics will provide a detailed introduction to the main informatics topics that underpin the various LC-MS/MS protocols used for protein identification and quantitation.

The handling and analysis of data generated by proteomics investigations represent a challenge for computer scientists, biostatisticians, and biologists to develop tools for storing, retrieving, visualizing, and analyzing genomic data. Informatics in Proteomics examines the ongoing advances in the application of bioinformatics to proteomics researc

This new third edition updates a best-selling encyclopedia. It includes about 56% more words than the 1,392-page second edition of 2003. The number of illustrations increased to almost 2,000 and their quality has improved by design and four colors. It includes approximately 1,800 current databases and web servers. This encyclopedia covers the basics and the latest in genomics, proteomics, genetic engineering, small RNAs, transcription factories, chromosome territories, stem cells, genetic networks, epigenetics, prions, hereditary diseases, and patents. Similar integrated information is not available in textbooks or on the Internet.

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.

Metabolomics and proteomics allow deep insights into the chemistry and physiology of biological systems. This book expounds open-source programs, platforms and programming tools for analysing metabolomics and proteomics mass spectrometry data. In contrast to commercial software, open-source software is created by the academic community, which facilitates the direct interaction between users and developers and accelerates the implementation of new concepts and ideas. The first section of the book covers the basics of mass spectrometry, experimental strategies, data operations, the open-source philosophy, metabolomics, proteomics and statistics/ data mining. In the second section, active programmers and users describe available software packages. Included tutorials, datasets and code examples can be used for training and for building custom workflows. Finally, every reader is invited to participate in the open science movement.

Introduction to the proteome (K. L. Williams, D. F. Hochstrasser). Two-dimensional electrophoresis: the state of the art and future directions (B. R. Herbert, J.-C. Sanchez, L. Bini). large-scale comparative protein modeling ( M. C. Peitsch, N. Guex); Clinical and biomedical applications of proteomics (D. F. Hochstrasser). Biological applications of proteomics (K. L. Williams, V. Pallini). Conclusions (D. F. Hochstrasser, L. Williams). Index.