Download or read book Computational and Statistical Methods for Protein Quantification by Mass Spectrometry written by Ingvar Eidhammer and published by John Wiley & Sons. This book was released on 2012-12-10 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive introduction to data analysis in quantitative proteomics This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers. Computational and Statistical Methods for Protein Quantification by Mass Spectrometry: Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs. Is illustrated by a large number of figures and examples as well as numerous exercises. Provides both clear and rigorous descriptions of methods and approaches. Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work. Features detailed discussions of both wet-lab approaches and statistical and computational methods. With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.

Download or read book Statistical Analysis of Proteomics Metabolomics and Lipidomics Data Using Mass Spectrometry written by Susmita Datta and published by Springer. This book was released on 2016-12-15 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Computational Methods for Mass Spectrometry Proteomics written by Ingvar Eidhammer and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Statistical Methods for the Analysis of Mass Spectrometry based Proteomics Data written by Xuan Wang and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Proteomics serves an important role at the systems-level in understanding of biological functioning. Mass spectrometry proteomics has become the tool of choice for identifying and quantifying the proteome of an organism. In the most widely used bottom-up approach to MS-based high-throughput quantitative proteomics, complex mixtures of proteins are first subjected to enzymatic cleavage, the resulting peptide products are separated based on chemical or physical properties and then analyzed using a mass spectrometer. The three fundamental challenges in the analysis of bottom-up MS-based proteomics are as follows: (i) Identifying the proteins that are present in a sample, (ii) Aligning different samples on elution (retention) time, mass, peak area (intensity) and etc, (iii) Quantifying the abundance levels of the identified proteins after alignment. Each of these challenges requires knowledge of the biological and technological context that give rise to the observed data, as well as the application of sound statistical principles for estimation and inference. In this dissertation, we present a set of statistical methods in bottom-up proteomics towards protein identification, alignment and quantification. We describe a fully Bayesian hierarchical modeling approach to peptide and protein identification on the basis of MS/MS fragmentation patterns in a unified framework. Our major contribution is to allow for dependence among the list of top candidate PSMs, which we accomplish with a Bayesian multiple component mixture model incorporating decoy search results and joint estimation of the accuracy of a list of peptide identifications for each MS/MS fragmentation spectrum. We also propose an objective criteria for the evaluation of the False Discovery Rate (FDR) associated with a list of identifications at both peptide level, which results in more accurate FDR estimates than existing methods like PeptideProphet. Several alignment algorithms have been developed using different warping functions. However, all the existing alignment approaches suffer from a useful metric for scoring an alignment between two data sets and hence lack a quantitative score for how good an alignment is. Our alignment approach uses "Anchor points" found to align all the individual scan in the target sample and provides a framework to quantify the alignment, that is, assigning a p-value to a set of aligned LC-MS runs to assess the correctness of alignment. After alignment using our algorithm, the p-values from Wilcoxon signed-rank test on elution (retention) time, M/Z, peak area successfully turn into non-significant values. Quantitative mass spectrometry-based proteomics involves statistical inference on protein abundance, based on the intensities of each protein's associated spectral peaks. However, typical mass spectrometry-based proteomics data sets have substantial proportions of missing observations, due at least in part to censoring of low intensities. This complicates intensity-based differential expression analysis. We outline a statistical method for protein differential expression, based on a simple Binomial likelihood. By modeling peak intensities as binary, in terms of "presence / absence", we enable the selection of proteins not typically amendable to quantitative analysis; e.g., "one-state" proteins that are present in one condition but absent in another. In addition, we present an analysis protocol that combines quantitative and presence / absence analysis of a given data set in a principled way, resulting in a single list of selected proteins with a single associated FDR.

Download or read book Quantitative Methods in Proteomics written by Katrin Marcus and published by Humana. This book was released on 2021-05-06 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition provides new and updated methods on the principles underlying modern protein analysis, from statistical issues to gel-based and mass spectrometry-based applications. Chapters detail protein quantification as basis for realisation of quantitative studies, gel-based and mass spectrometry-based quantification techniques, TMT, IPTL, PRM, MALDI Imaging, SILAC, PTM analysis, DIA, cross-linking, and the up-to-date topics of software and 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. Authoritative and cutting-edge, Quantitative Methods in Proteomics, Second Edition aims to provide comprehensive and competent overview in the important and still growing field of quantitative proteomics.

Download or read book Mass Spectrometry Data Analysis in Proteomics written by Rune Matthiesen and published by Humana. This book was released on 2019-10-01 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this new edition is to provide detailed information on each topic and present novel ideas and views that can influence future developments in mass spectrometry-based proteomics. In contrast to the previous editions, this third edition aims to provide the most relevant computational methods, focusing on computational concepts. 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. Authoritative and cutting-edge, Mass Spectrometry Data Analysis in Proteomics, Third Edition to ensure successful results in the further study of this vital field.

Download or read book Mass Spectrometry Analysis for Protein Protein Interactions and Dynamics written by M. Chance and published by John Wiley & Sons. This book was released on 2008-09-22 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a wide variety of mass spectrometry methods used to explore structural mechanisms, protein dynamics and interactions between proteins. Preliminary chapters cover mass spectrometry methods for examining proteins and are then followed by chapters devoted to presenting very practical, how-to methods in a detailed way. Includes footprinting and plistex specifically, setting this book apart from the competition.

Download or read book Selected Reaction Monitoring Mass Spectrometry SRM MS in Proteomics written by Mahmud Hossain and published by Springer Nature. This book was released on 2020-09-26 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering a wide-ranging facet of a “gold-standard” targeted mass spectrometry (MS) method for the consistent detection and accurate quantification of preselected proteins in complex biological matrices, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) in Proteomics: A Comprehensive View describes: The knowledge-based development of highly efficient SRM methodology including assay workflow, selection of proteins, peptides, transitions and its validation, and quality assessment Available bioinformatic tools – for both pre-acquisition method development and post-MS acquisition data analysis and data repositories Various relative and absolute quantification techniques SRM-MS’ widespread applications in biomarker development and in clinical studies, as well as in the analysis of various posttranslational modifications (PTMs) Current challenges and contemporary trends to overcome those difficulties In addition, it features the historical development of modern-day mass spectrometry with its vivid applications and also covers basic MS instrumentation, ionization techniques, and various proteomics approaches. Comprehensive discussion, extensive references at the end of each chapter, and the list of review articles in the bibliography offer invaluable resources for advanced readings. Researchers from the undergraduate to postgraduate level and beyond in both academic or industry settings studying and working on mass spectrometry and/or proteomics will benefit from this book.

Download or read book HT MS Tools for Data Quantification written by Joanne Ava and published by . This book was released on 2023-10-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proteomics Data Analysis written by Daniela Cecconi and published by . This book was released on 2021 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Separation Techniques Applied to Omics Sciences written by Ana Valéria Colnaghi Simionato and published by Springer Nature. This book was released on 2021-10-09 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers liquid chromatography, gas chromatography and capillary electrophoresis, the three main separation techniques lately available, applied to key omic sciences, such as genomics, proteomics, metabolomics and foodomics. The fundamentals of each technique are not covered herein. Instead, the recent advances in such techniques are presented focusing on the application to omics analyses and unique aspects in each case. This volume intends to offer wide ranging options available to researchers on omics sciences, and how to integrate them in order to achieve the comprehension of a biological system as a whole. Omic sciences have been of ultimate importance to comprehend the complex biochemical reactions and related events that occurs upon a biological system. The classical central dogma of molecular biology, which states that genetic information flows unidirectionally from DNA to RNA and then to proteins, has been gradually replaced by the systems biology approach. This book presents a multidisciplinary approach that explains the biological system as a whole, where the entire organism is influenced by a variety of internal events as well as by the environment, showing that each level of the biological information flux may influence the previous or the subsequent one.

Download or read book Systems Biology in Toxicology and Environmental Health written by Rebecca Fry and published by Academic Press. This book was released on 2015-06-11 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems Biology in Toxicology and Environmental Health uses a systems biological perspective to detail the most recent findings that link environmental exposures to human disease, providing an overview of molecular pathways that are essential for cellular survival after exposure to environmental toxicants, recent findings on gene-environment interactions influencing environmental agent-induced diseases, and the development of computational methods to predict susceptibility to environmental agents. Introductory chapters on molecular and cellular biology, toxicology and computational biology are included as well as an assessment of systems-based tools used to evaluate environmental health risks. Further topics include research on environmental toxicants relevant to human health and disease, various high-throughput technologies and computational methods, along with descriptions of the biological pathways associated with disease and the developmental origins of disease as they relate to environmental contaminants. Systems Biology in Toxicology and Environmental Health is an essential reference for undergraduate students, graduate students, and researchers looking for an introduction in the use of systems biology approaches to assess environmental exposures and their impacts on human health. - Provides the first reference of its kind, demonstrating the application of systems biology in environmental health and toxicology - Includes introductions to the diverse fields of molecular and cellular biology, toxicology, and computational biology - Presents a foundation that helps users understand the connections between the environment and health effects, and the biological mechanisms that link them

Download or read book Novel Computational Methods for Mass Spectrometry Based Protein Identification written by Rachana Jain and published by . This book was released on 2010 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mass spectrometry (MS) is used routinely to identify proteins in biological samples. Peptide Mass Fingerprinting (PMF) uses peptide masses and a pre-specified search database to identify proteins. It is often used as a complementary method along with Peptide Fragment Fingerprinting (PFF) or de-novo sequencing for increasing confidence and coverage of protein identification during mass spectrometric analysis. At the core of a PMF database search algorithm lies a similarity measure or quality statistics that is used to gauge the level to which an experimentally obtained peaklist agrees with a list of theoretically observable mass-to-charge ratios for a protein in a database. In this dissertation, we use publicly available gold standard data sets to show that the selection of search criteria such as mass tolerance and missed cleavages significantly affects the identification results. We propose, implement and evaluate a statistical (Kolmogorov-Smirnov-based) test which is computed for a large mass error threshold thus avoiding the choice of appropriate mass tolerance by the user. We use the mass tolerance identified by the Kolmogorov-Smirnov test for computing other quality measures. The results from our careful and extensive benchmarks suggest that the new method of computing the quality statistics without requiring the end-user to select a mass tolerance is competitive. We investigate the similarity measures in terms of their information content and conclude that the similarity measures are complementary and can be combined into a scoring function to possibly improve the over all accuracy of PMF based identification methods. We describe a new database search tool, PRIMAL, for protein identification using PMF. The novelty behind PRIMAL is two-fold. First, we comprehensively analyze methods for measuring the degree of similarity between experimental and theoretical peaklists. Second, we employ machine learning as a means of combining the individual similarity measures into a scoring function. Finally, we systematically test the efficacy of PRIMAL in identifying proteins using highly curated and publicly available data. Our results suggest that PRIMAL is competitive if not better than some of the tools extensively used by the mass spectrometry community. A web server with an implementation of the scoring function is available at http://bmi.cchmc.org/primal. We also note that the methodology is directly extensible to MS/MS based protein identification problem. We detail how to extend our approaches to the more complex MS/MS data.

Download or read book Biochemistry written by John T. Tansey and published by John Wiley & Sons. This book was released on 2020-07-15 with total page 994 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biochemistry: An Integrative Approach with Expanded Topics is addressed to premed, biochemistry, and life science majors taking a two-semester biochemistry course. This version includes all 25 chapters, offering a holistic approach to learning biochemistry. An integrated, skill-focused approach to the study of biochemistry and metabolism Biochemistry integrates subjects of interest to undergraduates majoring in premed, biochemistry, life science, and beyond, while preserving a chemical perspective. Respected biochemistry educator John Tansey takes a unique approach to the subject matter, emphasizing problem solving and critical thinking over rote memorization. Key concepts such as metabolism, are introduced and then revisited and cross-referenced throughout the text to establish pattern recognition and help students commit their new knowledge to long-term memory. As part of WileyPLUS, Biochemistry includes access to video walkthroughs of worked problems, interactive elements, and expanded end-of-chapter problems with a wide range of subject matter and difficulty. Students will have access to both qualitative and quantitative worked problems, and videos model the biochemical reasoning students will need to master. This approach helps students learn to analyze data and make critical assessments of experiments—key skills for success across scientific disciplines. Introduces students in scientific majors to the basics of biochemistry and metabolism Integrates and synthesizes topics throughout the text, allowing students to learn through repetition and pattern recognition Emphasizes problem solving and reasoning skills essential to life sciences, including data analysis and research assessment Provides access to video walkthroughs of worked problems, interactive features, and additional study material through WileyPLUS This volume covers DNA, RNA, gene regulation, synthetic proteins, omics, plant biochemistry, and more. With this text, students studying a range of disciplines are empowered to develop a lasting foundation in biochemistry and metabolism that will serve them as they advance through their careers.

Download or read book Statistical Analysis of Proteomic Data written by Thomas Burger and published by Springer Nature. This book was released on 2022-10-29 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the most important processing steps of proteomics data analysis and presents practical guidelines, as well as software tools, that are both user-friendly and state-of-the-art in chemo- and biostatistics. Beginning with methods to control the false discovery rate (FDR), the volume continues with chapters devoted to software suites for constructing quantitation data tables, missing value related issues, differential analysis software, and more. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and implementation advice that leads to successful results. Authoritative and practical, Statistical Analysis of Proteomic Data: Methods and Tools serves as an ideal guide for proteomics researchers looking to extract the best of their data with state-of-the art tools while also deepening their understanding of data analysis.

Download or read book Encyclopedia of Bioinformatics and Computational Biology written by and published by Elsevier. This book was released on 2018-08-21 with total page 3421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

Download or read book Statistical Methods for the Analysis of Mass Spectrometry Data written by Yuping Wu (Ph. D.) and published by . This book was released on 2006 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: