Computational and Statistical Methods for Protein Quantification by Mass Spectrometry

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.

In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Processes on a Network and Network Voronoi Diagrams, to Network K-function and Point Density Estimation Methods, and the Network Huff Model. The authors also discuss and illustrate the undertaking of the statistical tests described in a Geographical Information System (GIS) environment as well as demonstrating the user-friendly free software package SANET. Spatial Analysis Along Networks: Presents a much-needed practical guide to statistical spatial analysis of events on and alongside a network, in a logical, user-friendly order. Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics. Dedicates a separate chapter to each of the major techniques involved. Demonstrates the practicalities of undertaking the tests described in the book, using a GIS. Is supported by a supplementary website, providing readers with a link to the free software package SANET, so they can execute the statistical methods described in the book. Students and researchers studying spatial statistics, spatial analysis, geography, GIS, OR, traffic accident analysis, criminology, retail marketing, facility management and ecology will benefit from this book.

The authoritative guide to analyzing protein interactions by mass spectrometry Mass spectrometry (MS) is playing an increasingly important role in the study of protein interactions. Mass Spectrometry of Protein Interactionspresents timely and definitive discussions of the diverse range of approaches for studying protein interactions by mass spectrometry with an extensive set of references to the primary literature. Each chapter is written by authors or teams of authors who are international authorities in their fields. This leading reference text: * Discusses the direct detection of protein interactions through electrospray ionization (ESI-MS); ion mobility analysis; and matrix-assisted laser desorption/ionization (MALDI-MS) * Covers the indirect analysis of protein interactions through hydrogen-deuterium exchange (HX-MS); limited proteolysis; cross-linking; and radial probe (RP-MS) * Guides researchers in the use of mass spectrometry in structural biology, biochemistry, and protein science to map and define the huge number and diversity of protein interactions * Reviews the latest discoveries and applications and addresses new and ongoing challenges This is a comprehensive reference for researchers in academia and industry engaged in studies of protein interactions and an excellent text for graduate and postgraduate students.

Covers all major modifications, including phosphorylation, glycosylation, acetylation, ubiquitination, sulfonation and and glycation Discussion of the chemistry behind each modification, along with key methods and references Contributions from some of the leading researchers in the field A valuable reference source for all laboratories undertaking proteomics, mass spectrometry and post-translational modification research

Facilitates the discovery and development of new, effective therapeutics With coverage of the latest mass spectrometry technology, this book explains how mass spectrometry can be used to enhance almost all phases of drug discovery and drug development, including new and emerging applications. The book's fifteen chapters have been written by leading pharmaceutical and analytical scientists. Their contributions are based on a thorough review of the current literature as well as their own experience developing new mass spectrometry techniques to improve the ability to discover and develop new and effective therapeutics. Mass Spectrometry for Drug Discovery and Drug Development begins with an overview of the types of mass spectrometers that facilitate drug discovery and development. Next it covers: HPLC–high-resolution mass spectrometry for quantitative assays Mass spectrometry for siRNA Quantitative analysis of peptides Mass spectrometry analysis of biological drugs Applications that support medicinal chemistry investigations Mass spectrometry imaging and profiling Throughout the book, detailed examples underscore the growing role of mass spectrometry throughout the drug discovery and development process. In addition, images of mass spectra are provided to explain how results are interpreted. Extensive references at the end of each chapter guide readers to the primary literature in the field. Mass Spectrometry for Drug Discovery and Drug Development is recommended for readers in pharmaceutics, including medicinal chemists, analytical chemists, and drug metabolism scientists. All readers will discover how mass spectrometry can streamline and advance new drug discovery and development efforts.

Modelling has permeated virtually all areas of industrial, environmental, economic, bio-medical or civil engineering: yet the use of models for decision-making raises a number of issues to which this book is dedicated: How uncertain is my model ? Is it truly valuable to support decision-making ? What kind of decision can be truly supported and how can I handle residual uncertainty ? How much refined should the mathematical description be, given the true data limitations ? Could the uncertainty be reduced through more data, increased modeling investment or computational budget ? Should it be reduced now or later ? How robust is the analysis or the computational methods involved ? Should / could those methods be more robust ? Does it make sense to handle uncertainty, risk, lack of knowledge, variability or errors altogether ? How reasonable is the choice of probabilistic modeling for rare events ? How rare are the events to be considered ? How far does it make sense to handle extreme events and elaborate confidence figures ? Can I take advantage of expert / phenomenological knowledge to tighten the probabilistic figures ? Are there connex domains that could provide models or inspiration for my problem ? Written by a leader at the crossroads of industry, academia and engineering, and based on decades of multi-disciplinary field experience, Modelling Under Risk and Uncertainty gives a self-consistent introduction to the methods involved by any type of modeling development acknowledging the inevitable uncertainty and associated risks. It goes beyond the “black-box” view that some analysts, modelers, risk experts or statisticians develop on the underlying phenomenology of the environmental or industrial processes, without valuing enough their physical properties and inner modelling potential nor challenging the practical plausibility of mathematical hypotheses; conversely it is also to attract environmental or engineering modellers to better handle model confidence issues through finer statistical and risk analysis material taking advantage of advanced scientific computing, to face new regulations departing from deterministic design or support robust decision-making. Modelling Under Risk and Uncertainty: Addresses a concern of growing interest for large industries, environmentalists or analysts: robust modeling for decision-making in complex systems. Gives new insights into the peculiar mathematical and computational challenges generated by recent industrial safety or environmental control analysis for rare events. Implements decision theory choices differentiating or aggregating the dimensions of risk/aleatory and epistemic uncertainty through a consistent multi-disciplinary set of statistical estimation, physical modelling, robust computation and risk analysis. Provides an original review of the advanced inverse probabilistic approaches for model identification, calibration or data assimilation, key to digest fast-growing multi-physical data acquisition. Illustrated with one favourite pedagogical example crossing natural risk, engineering and economics, developed throughout the book to facilitate the reading and understanding. Supports Master/PhD-level course as well as advanced tutorials for professional training Analysts and researchers in numerical modeling, applied statistics, scientific computing, reliability, advanced engineering, natural risk or environmental science will benefit from this book.

Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.

The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing – there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This second edition of Statistical Methods for Food Science provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a ‘hands-on’ approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level. This revised and updated second edition is accompanied by a new companion website giving the reader access to the datasets and Excel spreadsheets featured in the book. Check it out now by visiting www.wiley.com/go/bower/statistical or by scanning the QR code below.

The book covers the application of numerical methods to reinforced concrete structures. To analyze reinforced concrete structures linear elastic theories are inadequate because of cracking, bond and the nonlinear and time dependent behavior of both concrete and reinforcement. These effects have to be considered for a realistic assessment of the behavior of reinforced concrete structures with respect to ultimate limit states and serviceability limit states. The book gives a compact review of finite element and other numerical methods. The key to these methods is through a proper description of material behavior. Thus, the book summarizes the essential material properties of concrete and reinforcement and their interaction through bond. These basics are applied to different structural types such as bars, beams, strut and tie models, plates, slabs and shells. This includes prestressing of structures, cracking, nonlinear stressstrain relations, creeping, shrinkage and temperature changes. Appropriate methods are developed for each structural type. Large displacement and dynamic problems are treated as well as short-term quasi-static problems and long-term transient problems like creep and shrinkage. Most problems are illustrated by examples which are solved by the program package ConFem, based on the freely available Python programming language. The ConFem source code together with the problem data is available under open source rules at concrete-fem.com. The author aims to demonstrate the potential and the limitations of numerical methods for simulation of reinforced concrete structures, addressing students, teachers, researchers and designing and checking engineers.

A concise, up-to-date overview of the applications of mass spectrometry To be able to estimate the potentiality of grapes and how it may be transferred into wine is key to grasping enological chemistry. Nowadays, mass spectrometry is a crucial aspect in ensuring the production, the quality, and the safety of grape, wine, and grape derivative products. Mass Spectrometry in Grape and Wine Chemistry examines in depth the relationship between the high structural identification power of mass spectrometry techniques and the chemistry of grapes and wine. The text is divided into two parts. The first section provides an overview of mass spectrometry methods in relation to enology in three chapters. The second section offers seven chapters on wine chemistry as well as traditional topics and new developments in mass spectrometry. Mass Spectrometry in Grape and Wine Chemistry explores many mass spectrometry applications, including: Ionization methods Mass analyzers and mass measurements Mass spectrometry methodologies Grape aroma compounds Volatile and aroma compounds in wines Grape and wine polyphenols Compounds released by wood into wine Wine defects caused by compounds Pesticide detection analysis Peptides and proteins of grape and wine Written by leading experts in the field, this book presents an introduction to mass spectrometry and outlines ways to maximize quality control and product safety for the best results. Mass Spectrometry in Grape and Wine Chemistry is an essential handbook for laboratories working in enology.