Estimation And Selection In High Dimensional Genomic Studies

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16th International Conference on Information Technology-New Generations (ITNG 2019)

Author : Shahram Latifi
Publisher : Springer
ISBN 13 : 3030140709
Total Pages : 652 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis 16th International Conference on Information Technology-New Generations (ITNG 2019) by : Shahram Latifi

Download or read book 16th International Conference on Information Technology-New Generations (ITNG 2019) written by Shahram Latifi and published by Springer. This book was released on 2019-05-22 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 16th International Conference on Information Technology - New Generations (ITNG), continues an annual event focusing on state of the art technologies pertaining to digital information and communications. The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security and health care are among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics. The conference features keynote speakers, the best student award, poster award, service award, a technical open panel, and workshops/exhibits from industry, government and academia.

Design and Analysis of Clinical Trials for Predictive Medicine

Author : Shigeyuki Matsui
Publisher : CRC Press
ISBN 13 : 1466558164
Total Pages : 394 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Design and Analysis of Clinical Trials for Predictive Medicine by : Shigeyuki Matsui

Download or read book Design and Analysis of Clinical Trials for Predictive Medicine written by Shigeyuki Matsui and published by CRC Press. This book was released on 2015-03-19 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming

Advanced Mean Field Methods

Author : Manfred Opper
Publisher : MIT Press
ISBN 13 : 9780262150545
Total Pages : 300 pages
Book Rating : 4.1/5 (55 download)

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Book Synopsis Advanced Mean Field Methods by : Manfred Opper

Download or read book Advanced Mean Field Methods written by Manfred Opper and published by MIT Press. This book was released on 2001 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling. A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

Handbook of Statistics in Clinical Oncology, Third Edition

Author : John Crowley
Publisher : CRC Press
ISBN 13 : 1439862001
Total Pages : 661 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Handbook of Statistics in Clinical Oncology, Third Edition by : John Crowley

Download or read book Handbook of Statistics in Clinical Oncology, Third Edition written by John Crowley and published by CRC Press. This book was released on 2012-03-26 with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many new challenges have arisen in the area of oncology clinical trials. New cancer therapies are often based on cytostatic or targeted agents, which pose new challenges in the design and analysis of all phases of trials. The literature on adaptive trial designs and early stopping has been exploding. Inclusion of high-dimensional data and imaging techniques have become common practice, and statistical methods on how to analyse such data have been refined in this area. A compilation of statistical topics relevant to these new advances in cancer research, this third edition of Handbook of Statistics in Clinical Oncology focuses on the design and analysis of oncology clinical trials and translational research. Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials, incorporating updates to all four parts: Phase I trials: Updated recommendations regarding the standard 3 + 3 and continual reassessment approaches, along with new chapters on phase 0 trials and phase I trial design for targeted agents. Phase II trials: Updates to current experience in single-arm and randomized phase II trial designs. New chapters include phase II designs with multiple strata and phase II/III designs. Phase III trials: Many new chapters include interim analyses and early stopping considerations, phase III trial designs for targeted agents and for testing the ability of markers, adaptive trial designs, cure rate survival models, statistical methods of imaging, as well as a thorough review of software for the design and analysis of clinical trials. Exploratory and high-dimensional data analyses: All chapters in this part have been thoroughly updated since the last edition. New chapters address methods for analyzing SNP data and for developing a score based on gene expression data. In addition, chapters on risk calculators and forensic bioinformatics have been added. Accessible to statisticians and oncologists interested in clinical trial methodology, the book is a single-source collection of up-to-date statistical approaches to research in clinical oncology.

Advances in Neural Information Processing Systems 15

Author : Suzanna Becker
Publisher : MIT Press
ISBN 13 : 9780262025508
Total Pages : 1738 pages
Book Rating : 4.0/5 (255 download)

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Book Synopsis Advances in Neural Information Processing Systems 15 by : Suzanna Becker

Download or read book Advances in Neural Information Processing Systems 15 written by Suzanna Becker and published by MIT Press. This book was released on 2003 with total page 1738 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the 2002 Neural Information Processing Systems Conference.

High-Dimensional Covariance Estimation

Author : Mohsen Pourahmadi
Publisher : John Wiley & Sons
ISBN 13 : 1118034295
Total Pages : 204 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis High-Dimensional Covariance Estimation by : Mohsen Pourahmadi

Download or read book High-Dimensional Covariance Estimation written by Mohsen Pourahmadi and published by John Wiley & Sons. This book was released on 2013-06-24 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and machine learning. Recently, the classical sample covariance methodologies have been modified and improved upon to meet the needs of statisticians and researchers dealing with large correlated datasets. High-Dimensional Covariance Estimation focuses on the methodologies based on shrinkage, thresholding, and penalized likelihood with applications to Gaussian graphical models, prediction, and mean-variance portfolio management. The book relies heavily on regression-based ideas and interpretations to connect and unify many existing methods and algorithms for the task. High-Dimensional Covariance Estimation features chapters on: Data, Sparsity, and Regularization Regularizing the Eigenstructure Banding, Tapering, and Thresholding Covariance Matrices Sparse Gaussian Graphical Models Multivariate Regression The book is an ideal resource for researchers in statistics, mathematics, business and economics, computer sciences, and engineering, as well as a useful text or supplement for graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.

Goodness-of-Fit Tests and Model Validity

Author : C. Huber-Carol
Publisher : Springer Science & Business Media
ISBN 13 : 1461201039
Total Pages : 512 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Goodness-of-Fit Tests and Model Validity by : C. Huber-Carol

Download or read book Goodness-of-Fit Tests and Model Validity written by C. Huber-Carol and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.

High-dimensional Data Analysis

Author : Tony Cai;Xiaotong Shen
Publisher :
ISBN 13 : 9787894236326
Total Pages : 318 pages
Book Rating : 4.2/5 (363 download)

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Book Synopsis High-dimensional Data Analysis by : Tony Cai;Xiaotong Shen

Download or read book High-dimensional Data Analysis written by Tony Cai;Xiaotong Shen and published by . This book was released on with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few years, significant developments have been taking place in highdimensional data analysis, driven primarily by a wide range of applications in many fields such as genomics and signal processing. In particular, substantial advances have been made in the areas of feature selection, covariance estimation, classification and regression. This book intends to examine important issues arising from highdimensional data analysis to explore key ideas for statistical inference and prediction. It is structured around topics on multiple hypothesis testing, feature selection, regression, cla.

Survival Analysis

Author : John P. Klein
Publisher : Springer Science & Business Media
ISBN 13 : 1475727283
Total Pages : 508 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Survival Analysis by : John P. Klein

Download or read book Survival Analysis written by John P. Klein and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.

Dynamic Regression Models for Survival Data

Author : Torben Martinussen
Publisher : Springer Science & Business Media
ISBN 13 : 0387339604
Total Pages : 471 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Dynamic Regression Models for Survival Data by : Torben Martinussen

Download or read book Dynamic Regression Models for Survival Data written by Torben Martinussen and published by Springer Science & Business Media. This book was released on 2007-11-24 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.

Statistical Analysis for High-Dimensional Data

Author : Arnoldo Frigessi
Publisher : Springer
ISBN 13 : 3319270990
Total Pages : 313 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Statistical Analysis for High-Dimensional Data by : Arnoldo Frigessi

Download or read book Statistical Analysis for High-Dimensional Data written by Arnoldo Frigessi and published by Springer. This book was released on 2016-02-16 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on future research directions, the contributions will benefit graduate students and researchers in computational biology, statistics and the machine learning community.

Evolution and Selection of Quantitative Traits

Author : Bruce Walsh
Publisher : Oxford University Press
ISBN 13 : 0192566644
Total Pages : 1504 pages
Book Rating : 4.1/5 (925 download)

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Book Synopsis Evolution and Selection of Quantitative Traits by : Bruce Walsh

Download or read book Evolution and Selection of Quantitative Traits written by Bruce Walsh and published by Oxford University Press. This book was released on 2018-06-21 with total page 1504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative traits-be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene-usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences.

Statistical Approaches in Omics Data Association Studies

Author : Qi Yan
Publisher : Frontiers Media SA
ISBN 13 : 2889763625
Total Pages : 169 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Statistical Approaches in Omics Data Association Studies by : Qi Yan

Download or read book Statistical Approaches in Omics Data Association Studies written by Qi Yan and published by Frontiers Media SA. This book was released on 2022-06-07 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Quantile Regression

Author : Roger Koenker
Publisher : CRC Press
ISBN 13 : 1498725295
Total Pages : 463 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Handbook of Quantile Regression by : Roger Koenker

Download or read book Handbook of Quantile Regression written by Roger Koenker and published by CRC Press. This book was released on 2017-10-12 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments. The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.

Fundamentals of Data Mining in Genomics and Proteomics

Author : Werner Dubitzky
Publisher : Springer Science & Business Media
ISBN 13 : 0387475095
Total Pages : 300 pages
Book Rating : 4.3/5 (874 download)

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Book Synopsis Fundamentals of Data Mining in Genomics and Proteomics by : Werner Dubitzky

Download or read book Fundamentals of Data Mining in Genomics and Proteomics written by Werner Dubitzky and published by Springer Science & Business Media. This book was released on 2007-04-13 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. It adopts an approach focusing on concepts and applications and presents key analytical techniques for the analysis of genomics and proteomics data by detailing their underlying principles, merits and limitations.

Computational Genomics with R

Author : Altuna Akalin
Publisher : CRC Press
ISBN 13 : 1498781861
Total Pages : 463 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Computational Genomics with R by : Altuna Akalin

Download or read book Computational Genomics with R written by Altuna Akalin and published by CRC Press. This book was released on 2020-12-16 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.

Advances in Statistical Bioinformatics

Author : Kim-Anh Do
Publisher : Cambridge University Press
ISBN 13 : 1107244919
Total Pages : 499 pages
Book Rating : 4.1/5 (72 download)

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Book Synopsis Advances in Statistical Bioinformatics by : Kim-Anh Do

Download or read book Advances in Statistical Bioinformatics written by Kim-Anh Do and published by Cambridge University Press. This book was released on 2013-06-10 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing genome-informed personalized treatment is a goal of modern medicine. Identifying new translational targets in nucleic acid characterizations is an important step toward that goal. The information tsunami produced by such genome-scale investigations is stimulating parallel developments in statistical methodology and inference, analytical frameworks, and computational tools. Within the context of genomic medicine and with a strong focus on cancer research, this book describes the integration of high-throughput bioinformatics data from multiple platforms to inform our understanding of the functional consequences of genomic alterations. This includes rigorous and scalable methods for simultaneously handling diverse data types such as gene expression array, miRNA, copy number, methylation, and next-generation sequencing data. This material is written for statisticians who are interested in modeling and analyzing high-throughput data. Chapters by experts in the field offer a thorough introduction to the biological and technical principles behind multiplatform high-throughput experimentation.