Statistical and Computational Pharmacogenomics PDF Download

Author: Rongling Wu
Publisher: CRC Press
ISBN: 1584888296
Category : Mathematics
Languages : en
Pages : 366

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Book Description
Due to the tremendous accumulation of data for genetic markers, pharmacogenomics, the study of the functions and interactions of all genes in the overall variability of drug response, is one of the hottest areas of research in biomedical science. Statistical and Computational Pharmacogenomics presents recent developments in statistical metho

Author: Russ Altman
Publisher: World Scientific
ISBN: 9789812702456
Category : Medical
Languages : en
Pages : 572

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Book Description
The Pacific Symposium on Biocomputing (PSB 2005) is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. This latest volume in the prestigious conference series contains the contributions of top researchers from the US, the Asia-Pacific region and around the world. Sections are devoted to databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. The book is an essential source of ideas, discoveries and references for academics in biocomputing, bioinformatics researchers and computer scientists.

Author: Russ B Altman
Publisher: World Scientific
ISBN: 9814481769
Category : Science
Languages : en
Pages : 565

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Book Description
The Pacific Symposium on Biocomputing (PSB 2005) is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. This latest volume in the prestigious conference series contains the contributions of top researchers from the US, the Asia-Pacific region and around the world. Sections are devoted to databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The book is an essential source of ideas, discoveries and references for academics in biocomputing, bioinformatics researchers and computer scientists.The proceedings have been selected for coverage in:

Author: Pierre Baldi
Publisher: MIT Press (MA)
ISBN: 9780262024426
Category : Biomolecules
Languages : en
Pages : 351

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Book Description
An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding more than ever. Biotechnology, pharmacology, and medicine will be particularly affected by the new results and the increased understanding of life at the molecular level. Bioinformatics is the development and application of computer methods for analysis, interpretation, and prediction, as well as for the design of experiments. It has emerged as a strategic frontier between biology and computer science. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory—and this is exactly the situation in molecular biology. As with its predecessor, statistical model fitting, the goal in machine learning is to extract useful information from a body of data by building good probabilistic models. The particular twist behind machine learning, however, is to automate the process as much as possible. In this book, Pierre Baldi and Soren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed at two types of researchers and students. First are the biologists and biochemists who need to understand new data-driven algorithms, such as neural networks and hidden Markov models, in the context of biological sequences and their molecular structure and function. Second are those with a primary background in physics, mathematics, statistics, or computer science who need to know more about specific applications in molecular biology.

Author: Rachel S. McCrea
Publisher: CRC Press
ISBN: 1439836590
Category : Mathematics
Languages : en
Pages : 316

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Book Description
An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the mortality and size of the populations. Capture-recapture methods are also used in other areas, including epidemiology and sociology. With an emphasis on ecology, Analysis of Capture-Recapture Data covers many modern developments of capture-recapture and related models and methods and places them in the historical context of research from the past 100 years. The book presents both classical and Bayesian methods. A range of real data sets motivates and illustrates the material and many examples illustrate biometry and applied statistics at work. In particular, the authors demonstrate several of the modeling approaches using one substantial data set from a population of great cormorants. The book also discusses which computer programs to use for implementing the models and contains 130 exercises that extend the main material. The data sets, computer programs, and other ancillaries are available at www.capturerecapture.co.uk. The book is accessible to advanced undergraduate and higher-level students, quantitative ecologists, and statisticians. It helps readers understand model formulation and applications, including the technicalities of model diagnostics and checking.

Author: Tohru Ozaki
Publisher: CRC Press
ISBN: 1420094610
Category : Mathematics
Languages : en
Pages : 561

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Book Description
Recent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required.Time Series Modeling of Neuroscience Data shows how to

Author: Stef van Buuren
Publisher: CRC Press
ISBN: 1439868247
Category : Mathematics
Languages : en
Pages : 344

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Book Description
Missing data form a problem in every scientific discipline, yet the techniques required to handle them are complicated and often lacking. One of the great ideas in statistical science—multiple imputation—fills gaps in the data with plausible values, the uncertainty of which is coded in the data itself. It also solves other problems, many of which are missing data problems in disguise. Flexible Imputation of Missing Data is supported by many examples using real data taken from the author's vast experience of collaborative research, and presents a practical guide for handling missing data under the framework of multiple imputation. Furthermore, detailed guidance of implementation in R using the author’s package MICE is included throughout the book. Assuming familiarity with basic statistical concepts and multivariate methods, Flexible Imputation of Missing Data is intended for two audiences: (Bio)statisticians, epidemiologists, and methodologists in the social and health sciences Substantive researchers who do not call themselves statisticians, but who possess the necessary skills to understand the principles and to follow the recipes This graduate-tested book avoids mathematical and technical details as much as possible: formulas are accompanied by a verbal statement that explains the formula in layperson terms. Readers less concerned with the theoretical underpinnings will be able to pick up the general idea, and technical material is available for those who desire deeper understanding. The analyses can be replicated in R using a dedicated package developed by the author.

Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309224187
Category : Science
Languages : en
Pages : 354

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Book Description
Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

Author: Rongling Wu
Publisher: CRC Press
ISBN: 0429528663
Category : Mathematics
Languages : en
Pages : 288

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Book Description
Modern medicine is undergoing a paradigm shift from a "one-size-fits-all" strategy to a more precise patient-customized therapy and medication plan. While the success of precision medicine relies on the level of pharmacogenomic knowledge, dissecting the genetic mechanisms of drug response in a sufficient detail requires powerful computational tools. Quantitative Methods for Precision Medicine: Pharmacogenomics in Action presents the advanced statistical methods for mapping pharmacogenetic control by integrating pharmacokinetic and pharmacodynamic principles of drug-body interactions. Beyond traditional reductionist-based statistical genetic approaches, statistical formulization in this book synthesizes elements of multiple disciplines to infer, visualize, and track how pharmacogenes interact together as an intricate but well-coordinated system to mediate patient-specific drug response. Features: Functional and systems mapping models to characterize the genetic architecture of multiple medication processes Statistical methods for analyzing informative missing data in pharmacogenetic association studies Functional graph theory of inferring genetic interaction networks from association data Leveraging the concept of epistasis to capture its bidirectional, signed and weighted properties Modeling gene-induced cell-cell crosstalk and its impact on drug response A graph model of drug-drug interactions in combination therapies Critical methodological issues to improve pharmacogenomic research as the cornerstone of precision medicine This book is suitable for graduate students and researchers in the fields of biology, medicine, bioinformatics and drug design and delivery who are interested in statistical and computational modelling of biological processes and systems. It may also serve as a major reference for applied mathematicians, computer scientists, and statisticians who attempt to develop algorithmic tools for genetic mapping, systems pharmacogenomics and systems biology. It can be used as both a textbook and research reference. Professionals in pharmaceutical sectors who design drugs and clinical doctors who deliver drugs will also find it useful.

Author: Ralitza Gueorguieva
Publisher: CRC Press
ISBN: 1498740774
Category : Mathematics
Languages : en
Pages : 371

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Book Description
Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. Features Provides an overview of intermediate to advanced statistical methods applied to psychiatry. Takes a non-technical approach with mathematical details kept to a minimum. Includes lots of detailed examples from published studies in psychiatry and related fields. Software programs, data sets and output are available on a supplementary website. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data. Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health. She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.