Multiple Testing Procedures With Applications To Genomics
DOWNLOAD
Download Multiple Testing Procedures With Applications To Genomics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Multiple Testing Procedures With Applications To Genomics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Multiple Testing Procedures With Applications To Genomics
DOWNLOAD
Author : Sandrine Dudoit
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-18
Multiple Testing Procedures With Applications To Genomics written by Sandrine Dudoit and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-18 with Computers categories.
This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. These are applied to a range of problems in biomedical and genomic research, including identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments; tests of association between gene expression measures and biological annotation metadata; sequence analysis; and genetic mapping of complex traits using single nucleotide polymorphisms. The procedures are based on a test statistics joint null distribution and provide Type I error control in testing problems involving general data generating distributions, null hypotheses, and test statistics.
Multiple Testing Procedures With Applications To Genomics
DOWNLOAD
Author : Sandrine Dudoit
language : en
Publisher: Springer
Release Date : 2008-11-01
Multiple Testing Procedures With Applications To Genomics written by Sandrine Dudoit and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-01 with Science categories.
This book establishes the theoretical foundations of a general methodology for multiple hypothesis testing and discusses its software implementation in R and SAS. These are applied to a range of problems in biomedical and genomic research, including identification of differentially expressed and co-expressed genes in high-throughput gene expression experiments; tests of association between gene expression measures and biological annotation metadata; sequence analysis; and genetic mapping of complex traits using single nucleotide polymorphisms. The procedures are based on a test statistics joint null distribution and provide Type I error control in testing problems involving general data generating distributions, null hypotheses, and test statistics.
Resampling Based Multiple Testing
DOWNLOAD
Author : Peter H. Westfall
language : en
Publisher: John Wiley & Sons
Release Date : 1993-01-12
Resampling Based Multiple Testing written by Peter H. Westfall and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-01-12 with Mathematics categories.
Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
Computational Genomics With R
DOWNLOAD
Author : Altuna Akalin
language : en
Publisher: CRC Press
Release Date : 2020-12-16
Computational Genomics With R written by Altuna Akalin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-16 with Mathematics categories.
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.
Encyclopedia Of Bioinformatics And Computational Biology
DOWNLOAD
Author :
language : en
Publisher: Elsevier
Release Date : 2018-08-21
Encyclopedia Of Bioinformatics And Computational Biology written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Medical categories.
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
Bioinformatics And Computational Biology Solutions Using R And Bioconductor
DOWNLOAD
Author : Robert Gentleman
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-29
Bioinformatics And Computational Biology Solutions Using R And Bioconductor written by Robert Gentleman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-29 with Computers categories.
Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R. All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Statistical Hypothesis Testing In Context
DOWNLOAD
Author : Michael P. Fay
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05
Statistical Hypothesis Testing In Context written by Michael P. Fay and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Mathematics categories.
This coherent guide equips applied statisticians to make good choices and proper interpretations in real investigations facing real data.
Advances In Financial Machine Learning
DOWNLOAD
Author : Marcos Lopez de Prado
language : en
Publisher: John Wiley & Sons
Release Date : 2018-01-23
Advances In Financial Machine Learning written by Marcos Lopez de Prado and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-23 with Business & Economics categories.
Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Medical And Health Genomics
DOWNLOAD
Author : Dhavendra Kumar
language : en
Publisher: Academic Press
Release Date : 2016-06-04
Medical And Health Genomics written by Dhavendra Kumar and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-04 with Science categories.
Medical and Health Genomics provides concise and evidence-based technical and practical information on the applied and translational aspects of genome sciences and the technologies related to non-clinical medicine and public health. Coverage is based on evolving paradigms of genomic medicine—in particular, the relation to public and population health genomics now being rapidly incorporated in health management and administration, with further implications for clinical population and disease management. - Provides extensive coverage of the emergent field of health genomics and its huge relevance to healthcare management - Presents user-friendly language accompanied by explanatory diagrams, figures, and many references for further study - Covers the applied, but non-clinical, sciences across disease discovery, genetic analysis, genetic screening, and prevention and management - Details the impact of clinical genomics across a diverse array of public and community health issues, and within a variety of global healthcare systems
Elements Of Data Science Machine Learning And Artificial Intelligence Using R
DOWNLOAD
Author : Frank Emmert-Streib
language : en
Publisher: Springer Nature
Release Date : 2023-10-03
Elements Of Data Science Machine Learning And Artificial Intelligence Using R written by Frank Emmert-Streib and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Technology & Engineering categories.
The textbook provides students with tools they need to analyze complex data using methods from data science, machine learning and artificial intelligence. The authors include both the presentation of methods along with applications using the programming language R, which is the gold standard for analyzing data. The authors cover all three main components of data science: computer science; mathematics and statistics; and domain knowledge. The book presents methods and implementations in R side-by-side, allowing the immediate practical application of the learning concepts. Furthermore, this teaches computational thinking in a natural way. The book includes exercises, case studies, Q&A and examples.