Exploration and Analysis of DNA Microarray and Other High-Dimensional Data
Exploration and Analysis of DNA Microarray and Other High-Dimensional Data

Author: Dhammika Amaratunga

Publisher: John Wiley & Sons

Published: 2014-01-27

Total Pages: 320

ISBN-13: 111836452X

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Praise for the First Edition “...extremely well written...a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.

Exploration and Analysis of DNA Microarray and Protein Array Data
Exploration and Analysis of DNA Microarray and Protein Array Data

Author: Dhammika Amaratunga

Publisher: John Wiley & Sons

Published: 2009-09-25

Total Pages: 270

ISBN-13: 0470317965

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A cutting-edge guide to the analysis of DNA microarray data Genomics is one of the major scientific revolutions of this century, and the use of microarrays to rapidly analyze numerous DNA samples has enabled scientists to make sense of mountains of genomic data through statistical analysis. Today, microarrays are being used in biomedical research to study such vital areas as a drug’s therapeutic value–or toxicity–and cancer-spreading patterns of gene activity. Exploration and Analysis of DNA Microarray and Protein Array Data answers the need for a comprehensive, cutting-edge overview of this important and emerging field. The authors, seasoned researchers with extensive experience in both industry and academia, effectively outline all phases of this revolutionary analytical technique, from the preprocessing to the analysis stage. Highlights of the text include: A review of basic molecular biology, followed by an introduction to microarrays and their preparation Chapters on processing scanned images and preprocessing microarray data Methods for identifying differentially expressed genes in comparative microarray experiments Discussions of gene and sample clustering and class prediction Extension of analysis methods to protein array data Numerous exercises for self-study as well as data sets and a useful collection of computational tools on the authors’ Web site make this important text a valuable resource for both students and professionals in the field.

Biopharmaceutical Applied Statistics Symposium
Biopharmaceutical Applied Statistics Symposium

Author: Karl E. Peace

Publisher: Springer

Published: 2018-09-03

Total Pages: 431

ISBN-13: 9811078203

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This BASS book Series publishes selected high-quality papers reflecting recent advances in the design and biostatistical analysis of biopharmaceutical experiments – particularly biopharmaceutical clinical trials. The papers were selected from invited presentations at the Biopharmaceutical Applied Statistics Symposium (BASS), which was founded by the first Editor in 1994 and has since become the premier international conference in biopharmaceutical statistics. The primary aims of the BASS are: 1) to raise funding to support graduate students in biostatistics programs, and 2) to provide an opportunity for professionals engaged in pharmaceutical drug research and development to share insights into solving the problems they encounter. The BASS book series is initially divided into three volumes addressing: 1) Design of Clinical Trials; 2) Biostatistical Analysis of Clinical Trials; and 3) Pharmaceutical Applications. This book is the third of the 3-volume book series. The topics covered include: Targeted Learning of Optimal Individualized Treatment Rules under Cost Constraints, Uses of Mixture Normal Distribution in Genomics and Otherwise, Personalized Medicine – Design Considerations, Adaptive Biomarker Subpopulation and Tumor Type Selection in Phase III Oncology Trials, High Dimensional Data in Genomics; Synergy or Additivity - The Importance of Defining the Primary Endpoint, Full Bayesian Adaptive Dose Finding Using Toxicity Probability Interval (TPI), Alpha-recycling for the Analyses of Primary and Secondary Endpoints of Clinical Trials, Expanded Interpretations of Results of Carcinogenicity Studies of Pharmaceuticals, Randomized Clinical Trials for Orphan Drug Development, Mediation Modeling in Randomized Trials with Non-normal Outcome Variables, Statistical Considerations in Using Images in Clinical Trials, Interesting Applications over 30 Years of Consulting, Uncovering Fraud, Misconduct and Other Data Quality Issues in Clinical Trials, Development and Evaluation of High Dimensional Prognostic Models, and Design and Analysis of Biosimilar Studies.

Applied Biclustering Methods for Big and High-Dimensional Data Using R
Applied Biclustering Methods for Big and High-Dimensional Data Using R

Author: Adetayo Kasim

Publisher: CRC Press

Published: 2016-10-03

Total Pages: 428

ISBN-13: 1482208245

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Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix. The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

Biochemistry and Molecular Biology Compendium
Biochemistry and Molecular Biology Compendium

Author: Roger L. Lundblad

Publisher: CRC Press

Published: 2019-11-11

Total Pages: 569

ISBN-13: 1351680536

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This book is an accessible resource offering practical information not found in more database-oriented resources. The first chapter lists acronyms with definitions, and a glossary of terms and subjects used in biochemistry, molecular biology, biotechnology, proteomics, genomics, and systems biology. There follows chapters on chemicals employed in biochemistry and molecular biology, complete with properties and structure drawings. Researchers will find this book to be a valuable tool that will save them time, as well as provide essential links to the roots of their science. Key selling features: Contains an extensive list of commonly used acronyms with definitions Offers a highly readable glossary for systems and techniques Provides comprehensive information for the validation of biotechnology assays and manufacturing processes Includes a list of Log P values, water solubility, and molecular weight for selected chemicals Gives a detailed listing of protease inhibitors and cocktails, as well as a list of buffers

GeNeDis 2020
GeNeDis 2020

Author: Panayiotis Vlamos

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 288

ISBN-13: 3030787753

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The 4th World Congress on Genetics, Geriatrics and Neurodegenerative Diseases Research (GeNeDis 2020) focuses on the latest major challenges in scientific research, new drug targets, the development of novel biomarkers, new imaging techniques, novel protocols for early diagnosis of neurodegenerative diseases, and several other scientific advances, with the aim of better, safer, and healthier aging. Computational methodologies for implementation on the discovery of biomarkers for neurodegenerative diseases are extensively discussed. This volume focuses on the sessions from the conference regarding computational biology and bioinformatics.

Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators

Author: Tailen Hsing

Publisher: John Wiley & Sons

Published: 2015-03-16

Total Pages: 368

ISBN-13: 1118762568

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Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA). The self–contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self–adjoint and non self–adjoint operators. The probabilistic foundation for FDA is described from the perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principal components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis. This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.

Correspondence Analysis
Correspondence Analysis

Author: Eric J. Beh

Publisher: John Wiley & Sons

Published: 2014-09-04

Total Pages: 646

ISBN-13: 1118762908

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A comprehensive overview of the internationalisation of correspondence analysis Correspondence Analysis: Theory, Practice and New Strategies examines the key issues of correspondence analysis, and discusses the new advances that have been made over the last 20 years. The main focus of this book is to provide a comprehensive discussion of some of the key technical and practical aspects of correspondence analysis, and to demonstrate how they may be put to use. Particular attention is given to the history and mathematical links of the developments made. These links include not just those major contributions made by researchers in Europe (which is where much of the attention surrounding correspondence analysis has focused) but also the important contributions made by researchers in other parts of the world. Key features include: A comprehensive international perspective on the key developments of correspondence analysis. Discussion of correspondence analysis for nominal and ordinal categorical data. Discussion of correspondence analysis of contingency tables with varying association structures (symmetric and non-symmetric relationship between two or more categorical variables). Extensive treatment of many of the members of the correspondence analysis family for two-way, three-way and multiple contingency tables. Correspondence Analysis offers a comprehensive and detailed overview of this topic which will be of value to academics, postgraduate students and researchers wanting a better understanding of correspondence analysis. Readers interested in the historical development, internationalisation and diverse applicability of correspondence analysis will also find much to enjoy in this book.

Time Series Analysis
Time Series Analysis

Author: George E. P. Box

Publisher: John Wiley & Sons

Published: 2015-05-29

Total Pages: 709

ISBN-13: 1118674928

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Praise for the Fourth Edition "The book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to model building, estimation, forecasting and control." —Mathematical Reviews Bridging classical models and modern topics, the Fifth Edition of Time Series Analysis: Forecasting and Control maintains a balanced presentation of the tools for modeling and analyzing time series. Also describing the latest developments that have occurred in the field over the past decade through applications from areas such as business, finance, and engineering, the Fifth Edition continues to serve as one of the most influential and prominent works on the subject. Time Series Analysis: Forecasting and Control, Fifth Edition provides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic models for time series and describes their use in five important areas of application: forecasting; determining the transfer function of a system; modeling the effects of intervention events; developing multivariate dynamic models; and designing simple control schemes. Along with these classical uses, the new edition covers modern topics with new features that include: A redesigned chapter on multivariate time series analysis with an expanded treatment of Vector Autoregressive, or VAR models, along with a discussion of the analytical tools needed for modeling vector time series An expanded chapter on special topics covering unit root testing, time-varying volatility models such as ARCH and GARCH, nonlinear time series models, and long memory models Numerous examples drawn from finance, economics, engineering, and other related fields The use of the publicly available R software for graphical illustrations and numerical calculations along with scripts that demonstrate the use of R for model building and forecasting Updates to literature references throughout and new end-of-chapter exercises Streamlined chapter introductions and revisions that update and enhance the exposition Time Series Analysis: Forecasting and Control, Fifth Edition is a valuable real-world reference for researchers and practitioners in time series analysis, econometrics, finance, and related fields. The book is also an excellent textbook for beginning graduate-level courses in advanced statistics, mathematics, economics, finance, engineering, and physics.

Time Series Forecasting
Time Series Forecasting

Author: Douglas C. Montgomery

Publisher: John Wiley & Sons

Published: 2024-07-30

Total Pages: 740

ISBN-13: 139418669X

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Bring the latest statistical tools to bear on predicting future variables and outcomes A huge range of fields rely on forecasts of how certain variables and causal factors will affect future outcomes, from product sales to inflation rates to demographic changes. Time series analysis is the branch of applied statistics which generates forecasts, and its sophisticated use of time oriented data can vastly impact the quality of crucial predictions. The latest computing and statistical methodologies are constantly being sought to refine these predictions and increase the confidence with which important actors can rely on future outcomes. Time Series Analysis and Forecasting presents a comprehensive overview of the methodologies required to produce these forecasts with the aid of time-oriented data sets. The potential applications for these techniques are nearly limitless, and this foundational volume has now been updated to reflect the most advanced tools. The result, more than ever, is an essential introduction to a core area of statistical analysis. Readers of the third edition of Time Series Analysis and Forecasting will also find: Updates incorporating JMP, SAS, and R software, with new examples throughout Over 300 exercises and 50 programming algorithms that balance theory and practice Supplementary materials in the e-book including solutions to many problems, data sets, and brand-new explanatory videos covering the key concepts and examples from each chapter. Time Series Analysis and Forecasting is ideal for graduate and advanced undergraduate courses in the areas of data science and analytics and forecasting and time series analysis. It is also an outstanding reference for practicing data scientists.