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Statistical Models For Removing Microarray Batch Effects And Analyzing Genome Tiling Microarrays
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Book Synopsis Nutrition and Management of Animals We Keep as Companions by : Anna Katharine Shoveller
Download or read book Nutrition and Management of Animals We Keep as Companions written by Anna Katharine Shoveller and published by Frontiers Media SA. This book was released on 2021-11-25 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Epigenetic Epidemiology by : Karin B. Michels
Download or read book Epigenetic Epidemiology written by Karin B. Michels and published by Springer Science & Business Media. This book was released on 2012-01-02 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: The exploding field of epigenetics is challenging the dogma of traditional Mendelian inheritance. Epigenetics plays an important role in shaping who we are and contributes to our prospects of health and disease. While early epigenetic research focused on plant and animal models and in vitro experiments, population-based epidemiologic studies increasingly incorporate epigenetic components. The relevance of epigenetic marks, such as DNA methylation, genomic imprinting, and histone modification for disease causation has yet to be fully explored.This book covers the basic concepts of epigenetic epidemiology, discusses challenges in study design, analysis, and interpretation, epigenetic laboratory techniques, the influence of age and environmental factors on shaping the epigenome, the role of epigenetics in the developmental origins hypothesis, and provides the state of the art on the epigenetic epidemiology of various health conditions including childhood syndromes, cancer, infectious diseases, inflammation and rheumatoid arthritis, asthma, autism and other neurodevelopmental disorders, psychiatric disorders, diabetes, obesity and metabolic disorders, and atherosclerosis. With contributions from: Peter Jones, Jean-Pierre Issa, Gavin Kelsey, Robert Waterland, and many other experts in epigenetics!
Book Synopsis Statistical Foundations of Data Science by : Jianqing Fan
Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 974 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
Book Synopsis Basics of Bioinformatics by : Rui Jiang
Download or read book Basics of Bioinformatics written by Rui Jiang and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines 11 courses and 15 research topics in bioinformatics, based on curriculums and talks in a graduate summer school on bioinformatics that was held in Tsinghua University. The courses include: Basics for Bioinformatics, Basic Statistics for Bioinformatics, Topics in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics Research, Association Analysis for Human Diseases: Methods and Examples, Data Mining and Knowledge Discovery Methods with Case Examples, Applied Bioinformatics Tools, Foundations for the Study of Structure and Function of Proteins, Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine, and Advanced Topics in Bioinformatics and Computational Biology. This book can serve as not only a primer for beginners in bioinformatics, but also a highly summarized yet systematic reference book for researchers in this field. Rui Jiang and Xuegong Zhang are both professors at the Department of Automation, Tsinghua University, China. Professor Michael Q. Zhang works at the Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Book Synopsis Genome Data Analysis by : Ju Han Kim
Download or read book Genome Data Analysis written by Ju Han Kim and published by Springer. This book was released on 2019-04-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.
Book Synopsis Microarray Bioinformatics by : Dov Stekel
Download or read book Microarray Bioinformatics written by Dov Stekel and published by Cambridge University Press. This book was released on 2003-09-08 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide to all of the mathematics, statistics and computing you will need to successfully operate DNA microarray experiments. It is written for researchers, clinicians, laboratory heads and managers, from both biology and bioinformatics backgrounds, who work with, or who intend to work with microarrays. The book covers all aspects of microarray bioinformatics, giving you the tools to design arrays and experiments, to analyze your data, and to share your results with your organisation or with the international community. There are chapters covering sequence databases, oligonucleotide design, experimental design, image processing, normalisation, identifying differentially expressed genes, clustering, classification and data standards. The book is based on the highly successful Microarray Bioinformatics course at Oxford University, and therefore is ideally suited for teaching the subject at postgraduate or professional level.
Book Synopsis Microarray Gene Expression Data Analysis by : Helen Causton
Download or read book Microarray Gene Expression Data Analysis written by Helen Causton and published by John Wiley & Sons. This book was released on 2009-04-01 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays
Book Synopsis Bioinformatics for Omics Data by : Bernd Mayer
Download or read book Bioinformatics for Omics Data written by Bernd Mayer and published by Springer Science+Business Media. This book was released on 2011-01-01 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting an area of research that intersects with and integrates diverse disciplines, Bioinformatics for Omics Data: Methods and Protocols collects contributions from expert researchers in order to provide practical guidelines to this complex study.
Book Synopsis Introduction to Single Cell Omics by : Xinghua Pan
Download or read book Introduction to Single Cell Omics written by Xinghua Pan and published by Frontiers Media SA. This book was released on 2019-09-19 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: Single-cell omics is a progressing frontier that stems from the sequencing of the human genome and the development of omics technologies, particularly genomics, transcriptomics, epigenomics and proteomics, but the sensitivity is now improved to single-cell level. The new generation of methodologies, especially the next generation sequencing (NGS) technology, plays a leading role in genomics related fields; however, the conventional techniques of omics require number of cells to be large, usually on the order of millions of cells, which is hardly accessible in some cases. More importantly, harnessing the power of omics technologies and applying those at the single-cell level are crucial since every cell is specific and unique, and almost every cell population in every systems, derived in either vivo or in vitro, is heterogeneous. Deciphering the heterogeneity of the cell population hence becomes critical for recognizing the mechanism and significance of the system. However, without an extensive examination of individual cells, a massive analysis of cell population would only give an average output of the cells, but neglect the differences among cells. Single-cell omics seeks to study a number of individual cells in parallel for their different dimensions of molecular profile on genome-wide scale, providing unprecedented resolution for the interpretation of both the structure and function of an organ, tissue or other system, as well as the interaction (and communication) and dynamics of single cells or subpopulations of cells and their lineages. Importantly single-cell omics enables the identification of a minor subpopulation of cells that may play a critical role in biological process over a dominant subpolulation such as a cancer and a developing organ. It provides an ultra-sensitive tool for us to clarify specific molecular mechanisms and pathways and reveal the nature of cell heterogeneity. Besides, it also empowers the clinical investigation of patients when facing a very low quantity of cell available for analysis, such as noninvasive cancer screening with circulating tumor cells (CTC), noninvasive prenatal diagnostics (NIPD) and preimplantation genetic test (PGT) for in vitro fertilization. Single-cell omics greatly promotes the understanding of life at a more fundamental level, bring vast applications in medicine. Accordingly, single-cell omics is also called as single-cell analysis or single-cell biology. Within only a couple of years, single-cell omics, especially transcriptomic sequencing (scRNA-seq), whole genome and exome sequencing (scWGS, scWES), has become robust and broadly accessible. Besides the existing technologies, recently, multiplexing barcode design and combinatorial indexing technology, in combination with microfluidic platform exampled by Drop-seq, or even being independent of microfluidic platform but using a regular PCR-plate, enable us a greater capacity of single cell analysis, switching from one single cell to thousands of single cells in a single test. The unique molecular identifiers (UMIs) allow the amplification bias among the original molecules to be corrected faithfully, resulting in a reliable quantitative measurement of omics in single cells. Of late, a variety of single-cell epigenomics analyses are becoming sophisticated, particularly single cell chromatin accessibility (scATAC-seq) and CpG methylation profiling (scBS-seq, scRRBS-seq). High resolution single molecular Fluorescence in situ hybridization (smFISH) and its revolutionary versions (ex. seqFISH, MERFISH, and so on), in addition to the spatial transcriptome sequencing, make the native relationship of the individual cells of a tissue to be in 3D or 4D format visually and quantitatively clarified. On the other hand, CRISPR/cas9 editing-based In vivo lineage tracing methods enable dynamic profile of a whole developmental process to be accurately displayed. Multi-omics analysis facilitates the study of multi-dimensional regulation and relationship of different elements of the central dogma in a single cell, as well as permitting a clear dissection of the complicated omics heterogeneity of a system. Last but not the least, the technology, biological noise, sequence dropout, and batch effect bring a huge challenge to the bioinformatics of single cell omics. While significant progress in the data analysis has been made since then, revolutionary theory and algorithm logics for single cell omics are expected. Indeed, single-cell analysis exert considerable impacts on the fields of biological studies, particularly cancers, neuron and neural system, stem cells, embryo development and immune system; other than that, it also tremendously motivates pharmaceutic RD, clinical diagnosis and monitoring, as well as precision medicine. This book hereby summarizes the recent developments and general considerations of single-cell analysis, with a detailed presentation on selected technologies and applications. Starting with the experimental design on single-cell omics, the book then emphasizes the consideration on heterogeneity of cancer and other systems. It also gives an introduction of the basic methods and key facts for bioinformatics analysis. Secondary, this book provides a summary of two types of popular technologies, the fundamental tools on single-cell isolation, and the developments of single cell multi-omics, followed by descriptions of FISH technologies, though other popular technologies are not covered here due to the fact that they are intensively described here and there recently. Finally, the book illustrates an elastomer-based integrated fluidic circuit that allows a connection between single cell functional studies combining stimulation, response, imaging and measurement, and corresponding single cell sequencing. This is a model system for single cell functional genomics. In addition, it reports a pipeline for single-cell proteomics with an analysis of the early development of Xenopus embryo, a single-cell qRT-PCR application that defined the subpopulations related to cell cycling, and a new method for synergistic assembly of single cell genome with sequencing of amplification product by phi29 DNA polymerase. Due to the tremendous progresses of single-cell omics in recent years, the topics covered here are incomplete, but each individual topic is excellently addressed, significantly interesting and beneficial to scientists working in or affiliated with this field.
Book Synopsis Statistical Analysis of Next Generation Sequencing Data by : Somnath Datta
Download or read book Statistical Analysis of Next Generation Sequencing Data written by Somnath Datta and published by Springer. This book was released on 2016-09-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized medicine. About the editors: Somnath Datta is Professor and Vice Chair of Bioinformatics and Biostatistics at the University of Louisville. He is Fellow of the American Statistical Association, Fellow of the Institute of Mathematical Statistics and Elected Member of the International Statistical Institute. He has contributed to numerous research areas in Statistics, Biostatistics and Bioinformatics. Dan Nettleton is Professor and Laurence H. Baker Endowed Chair of Biological Statistics in the Department of Statistics at Iowa State University. He is Fellow of the American Statistical Association and has published research on a variety of topics in statistics, biology and bioinformatics.
Book Synopsis The Analysis of Gene Expression Data by : Giovanni Parmigiani
Download or read book The Analysis of Gene Expression Data written by Giovanni Parmigiani and published by Springer Science & Business Media. This book was released on 2006-04-11 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.
Book Synopsis Applied Predictive Modeling by : Max Kuhn
Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
Book Synopsis Plant Systems Biology by : Sacha Baginsky
Download or read book Plant Systems Biology written by Sacha Baginsky and published by Springer Science & Business Media. This book was released on 2007-06-25 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume aims to provide a timely view of the state-of-the-art in systems biology. The editors take the opportunity to define systems biology as they and the contributing authors see it, and this will lay the groundwork for future studies. The volume is well-suited to both students and researchers interested in the methods of systems biology. Although the focus is on plant systems biology, the proposed material could be suitably applied to any organism.
Download or read book Archaea written by Roger A. Garrett and published by John Wiley & Sons. This book was released on 2008-05-12 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduced by Crafoord Prize winner Carl Woese, this volumecombines reviews of the major developments in archaeal researchover the past 10–15 years with more specialized articlesdealing with important recent breakthroughs. Drawing on majorthemes presented at the June 2005 meeting held in Munich to honorthe archaea pioneers Wolfram Zillig and Karl O. Stetter, the bookprovides a thorough survey of the field from its controversialbeginnings to its ongoing expansion to include aspects ofeukaryotic biology. The editors have assembled articles from the premier researchersin this rapidly burgeoning field, including an account by CarlWoese of his original discovery of the Archaea (until 1990 termedarchaebacteria) and the initially mixed reactions of the scientificcommunity. The review chapters and specialized articles address theemerging significance of the Archaea within a broader scientificand technological context, and include accounts of cutting-edgeresearch developments. The book spans archaeal evolution,physiology, and molecular and cellular biology and will be anessential reference for both graduate students and researchers.
Book Synopsis Gene Expression Technology by : David V. Goeddel
Download or read book Gene Expression Technology written by David V. Goeddel and published by . This book was released on 1990 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: The methods presented in this volume will enable the reader to design effective strategies for the expression of cloned genes and cDNAs and will prove useful in solving the majority of expression problems one is likely to encounter.
Book Synopsis Microarray Analysis of the Physical Genome by : Jonathan R. Pollack
Download or read book Microarray Analysis of the Physical Genome written by Jonathan R. Pollack and published by Humana Press. This book was released on 2010-07-09 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the early years of microarray technology, efforts were directed mainly at profiling expressed genes, while recently the microarray platform has been adapted into diverse applications directed toward the investigation of the physical genome. In Microarray Analysis of the Physical Genome: Methods and Protocols, experts in the field cover DNA microarray applications for the detection and characterization of genomic DNA-associated copy number alteration, loss of heterozygosity (LOH), cytosine methylation, protein binding sites, regulatory elements, and replication timing, with an emphasis on higher eukaryote (animal) and cancer genomes. Written in the highly successful Methods in Molecular BiologyTM series format, chapters include a brief introduction to their respective subjects, lists of the necessary materials and reagents, step-by-step protocols, and time-saving notes on troubleshooting and avoiding known pitfalls. Authoritative and easy-to-use, Microarray Analysis of the Physical Genome: Methods and Protocols is of great value to the molecular biologist or computational biologist interested in understanding the principles of these analyses or in planning future experiments using microarrays to characterize the physical genome.
Book Synopsis Deep Sequencing Data Analysis by : Noam Shomron
Download or read book Deep Sequencing Data Analysis written by Noam Shomron and published by Humana Press. This book was released on 2013-07-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new genetic revolution is fuelled by Deep Sequencing (or Next Generation Sequencing) apparatuses which, in essence, read billions of nucleotides per reaction. Effectively, when carefully planned, any experimental question which can be translated into reading nucleic acids can be applied.In Deep Sequencing Data Analysis, expert researchers in the field detail methods which are now commonly used to study the multi-facet deep sequencing data field. These included techniques for compressing of data generated, Chromatin Immunoprecipitation (ChIP-seq), and various approaches for the identification of sequence variants. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Deep Sequencing Data Analysis seeks to aid scientists in the further understanding of key data analysis procedures for deep sequencing data interpretation.
