Download or read book Statistical Inference and Classification for Mass Spectrometry MS Data written by Mourad Atlas and published by . This book was released on 2009 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mass spectrometry has emerged as a core technology for high throughput proteomics profiling in biomedical research. However, the complexity of the data poses new statistical challenges for the analysis. Statistical methods and software developments for analyzing proteomics data are likely to continue as a major area of research in the coming years. In this dissertation, we develop a novel statistical method for analyzing MS data. We propose to use the chemical knowledge regarding isotopic distribution of the peptide molecules along with quantitative modeling to detect chemically valuable peaks from each spectrum. More specifically, a mixture of location-shifted Poisson distribution is fitted to the deamidated isotopic distribution of a peptide molecule in low to moderate molecular weight of the mass spectrum. Maximum likelihood estimation by the expectation-maximization (EM) technique is used to estimate the parameters of the distribution. We then identify the monoisotopic peaks of the spectrum through formal statistical hypotheses testing procedures. Unlike low to moderate range MS data a Poisson distribution is not suitable for high mass ranges of the spectrum data due to symmetric nature of the isotopic distribution. Also, due to preprocessing and pronounced effect of the additional sources of variability, a Poisson approximation to the binomial model to the isotopic distribution may not hold. Therefore, a mixture of location-shifted Normal model is fitted to model each of the deamidated (possibly) isotopic distribution of a mass spectrum. A nonlinear optimization method to maximize the observed data likelihood is applied instead of EM algorithm to estimate the parameters of the distribution. Similar statistical testing procedures are applied for the peak detection method. A study of the effectiveness of our features selection method compared to some other relatively new feature selection methods in classifying case and control samples is explored. Superiority of our method is established in terms of the overall classification accuracy, sensitivity, specificity and area under the receptor operative curve (ROC) curve.
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 Mass Spectrometry Data Analysis in Proteomics written by Rune Matthiesen and published by Springer Science & Business Media. This book was released on 2008-02-02 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Analysis of Proteomic Mass Spectrometry Data for the Identification of Biomarkers and Disease Diagnosis written by Tyman Stanford and published by . This book was released on 2015 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proteomic spectra obtained from matrix-assisted laser desorption ionisation (MALDI) time-of-flight mass spectrometry (TOF-MS) are generated from the proteins and peptides present in serum obtained from blood. By ionising the proteins and resolving them in the mass spectrometer, data on the expression of proteins can be obtained, realised from the amplitude of signal for different mass to charge ratios. Of primary interest is the biological signal, in particular, the expression of proteins related to disease. In common with many 'omic' technologies, the raw spectra suffer from systematic errors due to technological artefacts and batch-effects, in addition to sample and biological variability. To negate these effects, novel application of genetic microarray pre-processing and analysis methods to proteomic TOF-MS data are presented. However, there are important differences between microarray and TOF-MS data which require consideration and non-trivial modifications to be successfully applied. One important difference between MALDI TOF-MS data and other high-throughput data, seldom addressed, is the high proportion of missing values. The pre-processing of raw proteomic TOF-MS data needs to be undertaken prior to analysis and remains a mathematical and statistical challenge. Performed in distinct steps, pre-processing consists of signal smoothing, baseline correction, spectra normalisation, peak detection and peak alignment. An argument as to why the order of these steps is highly important is presented. Standard and novel data pre-processing methods are investigated and compared to optimise the process. Each step is given due consideration since the cumulative effects of substandard pre-processing can render subsequent statistical analysis highly unreliable. Ultimately, the aim of proteomic MS is to analyse the protein profiles. Two different but related approaches to the analysis are undertaken. The first approach is to identify biological markers (biomarkers) that exhibit differential expression between disease groups. Identifying potential biomarkers for further research requires appropriate exploratory, visual and statistical modelling which is addressed in detail here. The second approach is to perform statistical discrimination between groups, a classical supervised learning problem. The ability of mathematical models to predict disease groups using differential biological signal provides insight into the plausibility of diagnostic tests. Methodologically, supervised learning is a multifaceted problem given that feature selection, model parameter optimisation, and the handling of the training and test data all contribute to the inference that can be made from the results. Empirical appraisal of the methods applied to the proteomic data are provided with the outcome of discrimination error as a quantitative benchmark. A number of proteomic TOF-MS datasets with differing characteristics are used throughout this thesis to assess the validity of the methods presented. The detailed analysis of a murine model MALDI TOF-MS dataset has facilitated the discovery of potential biomarkers for gastric cancer. Correct classification of spectra to their respective disease group (gastric cancer or control mice) as high as 97.4% was achieved using supervised learning. The thorough treatment of all the differently behaved datasets contained in this thesis, starting from the raw data pre-processing steps through to the challenging process of identifying potential biomarkers, provides a comprehensive and best-practice pipeline to analyse real-world proteomic MS data.
Download or read book Computational Methods in Biomedical Research written by Ravindra Khattree and published by CRC Press. This book was released on 2007-12-12 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continuing advances in biomedical research and statistical methods call for a constant stream of updated, cohesive accounts of new developments so that the methodologies can be properly implemented in the biomedical field. Responding to this need, Computational Methods in Biomedical Research explores important current and emerging computational statistical methods that are used in biomedical research. Written by active researchers in the field, this authoritative collection covers a wide range of topics. It introduces each topic at a basic level, before moving on to more advanced discussions of applications. The book begins with microarray data analysis, machine learning techniques, and mass spectrometry-based protein profiling. It then uses state space models to predict US cancer mortality rates and provides an overview of the application of multistate models in analyzing multiple failure times. The book also describes various Bayesian techniques, the sequential monitoring of randomization tests, mixed-effects models, and the classification rules for repeated measures data. The volume concludes with estimation methods for analyzing longitudinal data. Supplying the knowledge necessary to perform sophisticated statistical analyses, this reference is a must-have for anyone involved in advanced biomedical and pharmaceutical research. It will help in the quest to identify potential new drugs for the treatment of a variety of diseases.
Download or read book Statistics for Microarrays written by Ernst Wit and published by John Wiley & Sons. This book was released on 2004-07-23 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in microarrays has increased considerably in the last ten years. This increase in the use of microarray technology has led to the need for good standards of microarray experimental notation, data representation, and the introduction of standard experimental controls, as well as standard data normalization and analysis techniques. Statistics for Microarrays: Design, Analysis and Inference is the first book that presents a coherent and systematic overview of statistical methods in all stages in the process of analysing microarray data – from getting good data to obtaining meaningful results. Provides an overview of statistics for microarrays, including experimental design, data preparation, image analysis, normalization, quality control, and statistical inference. Features many examples throughout using real data from microarray experiments. Computational techniques are integrated into the text. Takes a very practical approach, suitable for statistically-minded biologists. Supported by a Website featuring colour images, software, and data sets. Primarily aimed at statistically-minded biologists, bioinformaticians, biostatisticians, and computer scientists working with microarray data, the book is also suitable for postgraduate students of bioinformatics.
Download or read book Introduction to Mass Spectrometry written by J. Throck Watson and published by John Wiley & Sons. This book was released on 2007-11-12 with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt: Completely revised and updated, this text provides an easy-to-read guide to the concept of mass spectrometry and demonstrates its potential and limitations. Written by internationally recognised experts and utilising "real life" examples of analyses and applications, the book presents real cases of qualitative and quantitative applications of mass spectrometry. Unlike other mass spectrometry texts, this comprehensive reference provides systematic descriptions of the various types of mass analysers and ionisation, along with corresponding strategies for interpretation of data. The book concludes with a comprehensive 3000 references. This multi-disciplined text covers the fundamentals as well as recent advance in this topic, providing need-to-know information for researchers in many disciplines including pharmaceutical, environmental and biomedical analysis who are utilizing mass spectrometry
Download or read book Machine Learning and Statistical Approaches to the Quality Classification of Tandem Mass Spectrometry written by Lijuan Mo and published by . This book was released on 2006 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book High Performance Algorithms for Mass Spectrometry Based Omics written by Fahad Saeed and published by Springer Nature. This book was released on 2022-09-02 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Simultaneous Statistical Inference written by Thorsten Dickhaus and published by Springer Science & Business Media. This book was released on 2014-01-23 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
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 Handbook of Forensic Statistics written by David L. Banks and published by CRC Press. This book was released on 2020-11-05 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Forensic Statistics is a collection of chapters by leading authorities in forensic statistics. Written for statisticians, scientists, and legal professionals having a broad range of statistical expertise, it summarizes and compares basic methods of statistical inference (frequentist, likelihoodist, and Bayesian) for trace and other evidence that links individuals to crimes, the modern history and key controversies in the field, and the psychological and legal aspects of such scientific evidence. Specific topics include uncertainty in measurements and conclusions; statistically valid statements of weight of evidence or source conclusions; admissibility and presentation of statistical findings; and the state of the art of methods (including problems and pitfalls) for collecting, analyzing, and interpreting data in such areas as forensic biology, chemistry, and pattern and impression evidence. The particular types of evidence that are discussed include DNA, latent fingerprints, firearms and toolmarks, glass, handwriting, shoeprints, and voice exemplars.
Download or read book Forensic Chemistry written by Jay A. Siegel and published by John Wiley & Sons. This book was released on 2015-10-05 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forensic Chemistry: Fundamentals and Applications presents a new approach to the study of applications of chemistry to forensic science. It is edited by one of the leading forensic scientists with each chapter written by international experts specializing in their respective fields, and presents the applications of chemistry, especially analytical chemistry, to various topics that make up the forensic scientists toolkit. This comprehensive, textbook includes in-depth coverage of the major topics in forensic chemistry including: illicit drugs, fibers, fire and explosive residues, soils, glass and paints, the chemistry of fingerprint recovery on porous surfaces, the chemistry of firearms analysis, as well as two chapters on the key tools of forensic science, microscopy and chemometrics. Each topic is explored at an advanced college level, with an emphasis, throughout the text, on the use of chemical tools in evidence analysis. Forensic Chemistry: Fundamentals and Applications is essential reading for advanced students of forensic science and analytical chemistry, as well as forensic science practitioners, researchers and faculty, and anyone who wants to learn about the fascinating subject of forensic chemistry in some depth. This book is published as part of the AAFS series 'Forensic Science in Focus'.
Download or read book Statistical Analysis of Mass Spectrometry Data written by Suaad Omran S. Ben-Farag and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modern Inference Based on Health Related Markers written by Albert Vexler and published by Academic Press. This book was released on 2024-03-18 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Inference Based on Health Related Markers: Biomarkers and Statistical Decision Making provides a compendium of biomarkers based methodologies for respective health related fields and health related marker-specific biostatistical techniques. These methodologies may be applied to various problems encountered in medical and epidemiological studies. This book introduces correct and efficient testing mechanisms including procedures based on bootstrap and permutation methods with the aim of making these techniques assessable to practical researchers. In the biostatistical aspect, it describes how to correctly state testing problems, but it also includes novel results, which have appeared in current statistical publications. The book discusses also modern applied statistical developments that consider data-driven techniques, including empirical likelihood methods and other simple and efficient methods to derive statistical tools for use in health related studies. The title is a valuable source for biostaticians, practitioners, theoretical and applied investigators, and several members of the biomedical field who are interested in learning more about efficient evidence-based inference incorporating several forms of markers measurements. Combines modern epidemiological and public health discoveries with cutting-edge biostatistical tools, including relevant software codes, offering one full package to meet the demand of practical investigators Includes the emerging topics from real health fields in order to display recent advances and trends in Biomarkers and associated Decision Making areas Written by researchers who are leaders of Epidemiological and Biostatistical fields, presenting up-to-date investigations related to the measuring health issues, emerging fields of biomarkers, designing health studies and their implementations, clinical trials and their practices and applications, different aspects of genetic markers
Download or read book Tietz Textbook of Laboratory Medicine E Book written by Nader Rifai and published by Elsevier Health Sciences. This book was released on 2022-02-03 with total page 4232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use THE definitive reference for laboratory medicine and clinical pathology! Tietz Textbook of Laboratory Medicine, 7th Edition provides the guidance necessary to select, perform, and evaluate the results of new and established laboratory tests. Comprehensive coverage includes the latest advances in topics such as clinical chemistry, genetic metabolic disorders, molecular diagnostics, hematology and coagulation, clinical microbiology, transfusion medicine, and clinical immunology. From a team of expert contributors led by Nader Rifai, this reference includes access to wide-ranging online resources on Expert Consult — featuring the comprehensive product with fully searchable text, regular content updates, animations, podcasts, over 1300 clinical case studies, lecture series, and more. Authoritative, current content helps you perform tests in a cost-effective, timely, and efficient manner; provides expertise in managing clinical laboratory needs; and shows how to be responsive to an ever-changing environment. Current guidelines help you select, perform, and evaluate the results of new and established laboratory tests. Expert, internationally recognized chapter authors present guidelines representing different practices and points of view. Analytical criteria focus on the medical usefulness of laboratory procedures. Use of standard and international units of measure makes this text appropriate for any user, anywhere in the world. Expert Consult provides the entire text as a fully searchable eBook, and includes regular content updates, animations, podcasts, more than 1300 clinical case studies, over 2500 multiple-choice questions, a lecture series, and more. NEW! 19 additional chapters highlight various specialties throughout laboratory medicine. NEW! Updated, peer-reviewed content provides the most current information possible. NEW! The largest-ever compilation of clinical cases in laboratory medicine is included on Expert Consult. NEW! Over 100 adaptive learning courses on Expert Consult offer the opportunity for personalized education.
Download or read book New Frontiers of Biostatistics and Bioinformatics written by Yichuan Zhao and published by Springer. This book was released on 2018-12-05 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas. Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners.
