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Download or read book Special Issue on Multivariate Methods in Genomic Data Analysis written by and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Henry Horng-Shing Lu
Publisher : Springer Science & Business Media
ISBN 13 : 3642163459
Total Pages : 621 pages
Book Rating : 4.6/5 (421 download)
Download or read book Handbook of Statistical Bioinformatics written by Henry Horng-Shing Lu and published by Springer Science & Business Media. This book was released on 2011-05-17 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
Author : Gary Hardiman
Publisher :
ISBN 13 : 9783039287451
Total Pages : 202 pages
Book Rating : 4.2/5 (874 download)
Download or read book Systems Analytics and Integration of Big Omics Data written by Gary Hardiman and published by . This book was released on 2020 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: A “genotype"" is essentially an organism's full hereditary information which is obtained from its parents. A ""phenotype"" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene-environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.
Author : Francisco A. Gómez Vela
Publisher :
ISBN 13 : 9783039437726
Total Pages : 222 pages
Book Rating : 4.4/5 (377 download)
Download or read book Computational Methods for the Analysis of Genomic Data and Biological Processes written by Francisco A. Gómez Vela and published by . This book was released on 2021 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent decades, new technologies have made remarkable progress in helping to understand biological systems. Rapid advances in genomic profiling techniques such as microarrays or high-performance sequencing have brought new opportunities and challenges in the fields of computational biology and bioinformatics. Such genetic sequencing techniques allow large amounts of data to be produced, whose analysis and cross-integration could provide a complete view of organisms. As a result, it is necessary to develop new techniques and algorithms that carry out an analysis of these data with reliability and efficiency. This Special Issue collected the latest advances in the field of computational methods for the analysis of gene expression data, and, in particular, the modeling of biological processes. Here we present eleven works selected to be published in this Special Issue due to their interest, quality, and originality.
Author : Jianqing Fan
Publisher : World Scientific
ISBN 13 : 1908979763
Total Pages : 552 pages
Book Rating : 4.9/5 (89 download)
Download or read book Frontiers In Statistics written by Jianqing Fan and published by World Scientific. This book was released on 2006-07-17 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical computing, generalized nonlinear regression and mixed effects models, martingale transform tests for model diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th birthday. The first article of this volume summarizes some of Prof. Bickel's distinguished contributions.
Author : Osval Antonio Montesinos López
Publisher : Springer Nature
ISBN 13 : 3030890104
Total Pages : 707 pages
Book Rating : 4.0/5 (38 download)
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Author : M. Henry Linder
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)
Download or read book Linear Methods for Joint Analysis of Multivariate Genomics Data written by M. Henry Linder and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The rise of Big Data has enabled sophisticated analysis of the human genome in unprecedented detail. Large datasets are now collected as a matter of routine, and their scope spans multiple data types and multiple functional units at the molecular level of the cell. The breadth and depth of these data offer the opportunity for complex experiments and extensive structural modeling. But, given the intricacies of these data and the nuanced challenges they pose, robust and rigorous methods are essential to ensure the value and validity of the resulting scientific research. In this dissertation, we consider statistical methods for networks, applied to signaling pathways in the human genome. We construct joint, integrative models that employ a variety of data types simultaneously. These pathway models provide a unified approach to analysis of genetic, epigenetic, transcriptomic, and other types of genomic data, and incorporate functionally meaningful biological relationships. In particular, we propose a new pathway model that integrates non-coding micro RNAs, proteins that play a regulatory role with respect to genes. We also propose methods to address obstacles that arise in the course of real-world research. We consider missing data, a fundamental reality of -omics Big Data due to variability in data quality and experimental design. We adapt a low-rank method for matrix completion to apply to bioinformatic datasets with arbitrary patterns of missing data. We apply the imputation and pathway methods to a large-scale research study that profiles more than 30 cancer types. We also propose an algorithm to identify important subnetworks within large signaling pathways, in order to hone our understanding of the drivers of complex diseases. Through the use of interactive data visualization and analysis, we promote access to -omics analyses. Taken together, these methods provide a suite of tools that empower biological research using -omics data. Our methods span functional genomic models, address real-world problems in data analysis, and seek to make analysis of complex datasets more tractable, all while maintaining a statistically sound foundation.
Author : Niall Adams
Publisher : Springer
ISBN 13 : 3319687654
Total Pages : 361 pages
Book Rating : 4.3/5 (196 download)
Download or read book Advances in Intelligent Data Analysis XVI written by Niall Adams and published by Springer. This book was released on 2017-10-20 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the conference proceedings of the 16th International Symposium on Intelligent Data Analysis, which was held in October 2017 in London, UK. The 28 full papers presented in this book were carefully reviewed and selected from 66 submissions. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. IDA solicits papers on all aspects of intelligent data analysis, including papers on intelligent support for modelling and analyzing data from complex, dynamical systems.
Author : Sophie Dabo-Niang
Publisher : Springer Science & Business Media
ISBN 13 : 3790820628
Total Pages : 296 pages
Book Rating : 4.7/5 (98 download)
Download or read book Functional and Operatorial Statistics written by Sophie Dabo-Niang and published by Springer Science & Business Media. This book was released on 2008-05-21 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: An increasing number of statistical problems and methods involve infinite-dimensional aspects. This is due to the progress of technologies which allow us to store more and more information while modern instruments are able to collect data much more effectively due to their increasingly sophisticated design. This evolution directly concerns statisticians, who have to propose new methodologies while taking into account such high-dimensional data (e.g. continuous processes, functional data, etc.). The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile. This book gathers important contributions on the functional and operatorial statistics fields.
Author : Hui Jiang
Publisher : MDPI
ISBN 13 : 3039361406
Total Pages : 136 pages
Book Rating : 4.0/5 (393 download)
Download or read book Statistical Methods for the Analysis of Genomic Data written by Hui Jiang and published by MDPI. This book was released on 2020-12-29 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, technological breakthroughs have greatly enhanced our ability to understand the complex world of molecular biology. Rapid developments in genomic profiling techniques, such as high-throughput sequencing, have brought new opportunities and challenges to the fields of computational biology and bioinformatics. Furthermore, by combining genomic profiling techniques with other experimental techniques, many powerful approaches (e.g., RNA-Seq, Chips-Seq, single-cell assays, and Hi-C) have been developed in order to help explore complex biological systems. As a result of the increasing availability of genomic datasets, in terms of both volume and variety, the analysis of such data has become a critical challenge as well as a topic of great interest. Therefore, statistical methods that address the problems associated with these newly developed techniques are in high demand. This book includes a number of studies that highlight the state-of-the-art statistical methods for the analysis of genomic data and explore future directions for improvement.
Author :
Publisher :
ISBN 13 :
Total Pages : 141 pages
Book Rating : 4.:/5 (878 download)
Download or read book Special Issue on Robust Multivariate Analysis and Classification written by and published by . This book was released on 2007 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Mohamed Megahed
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783659401817
Total Pages : 180 pages
Book Rating : 4.4/5 (18 download)
Download or read book Genomic Data Analysis written by Mohamed Megahed and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers some important methods for the analysis of micro-array data and QTL. It is also considered important that readers learn to read and understand the relevant literature, because it is a fast moving subject field. R and Bioconductor used in this book. The student can explore the dependencies and the structure in a large multivariate data set, and can apply the multivariate methods correctly. The reader can also analyze micro-arrays and he/she known the basics of QTL, linkage analysis and association studies. The reader is able to read and understand the relevant literature. Multivariate data analysis is basically a collection of many statistical methods that are applicable to large and/or high dimensional data sets. All methods that are covered in this book, are often applied in industry and research institutions.
Author : Dan Nettleton
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (17 download)
Download or read book Special Issue: Statistical Genomics and Transcriptomics in Agriculture written by Dan Nettleton and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Andrei Y. Yakovlev
Publisher : Humana Press
ISBN 13 : 9781493950799
Total Pages : 212 pages
Book Rating : 4.9/5 (57 download)
Download or read book Statistical Methods for Microarray Data Analysis written by Andrei Y. Yakovlev and published by Humana Press. This book was released on 2016-08-23 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Statistically,a microarray may be considered as an observation of very high dimensionality equal to the number of expression levels measured on it. In Statistical Methods for Microarray Data Analysis: Methods and Protocols, expert researchers in the field detail many methods and techniques used to study microarrays, guiding the reader from microarray technology to statistical problems of specific multivariate data analysis. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Statistical Methods for Microarray Data Analysis: Methods and Protocols aids scientists in continuing to study microarrays and the most current statistical methods.
Author : Daniel R. Fuhrmann
Publisher :
ISBN 13 :
Total Pages : 174 pages
Book Rating : 4.:/5 (249 download)
Download or read book Special Issue: Genomics, Signal Processing, and Statistics written by Daniel R. Fuhrmann and published by . This book was released on 2004 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gary Hardiman
Publisher : MDPI
ISBN 13 : 3039287443
Total Pages : 202 pages
Book Rating : 4.0/5 (392 download)
Download or read book Systems Analytics and Integration of Big Omics Data written by Gary Hardiman and published by MDPI. This book was released on 2020-04-15 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: A “genotype" is essentially an organism's full hereditary information which is obtained from its parents. A "phenotype" is an organism's actual observed physical and behavioral properties. These may include traits such as morphology, size, height, eye color, metabolism, etc. One of the pressing challenges in computational and systems biology is genotype-to-phenotype prediction. This is challenging given the amount of data generated by modern Omics technologies. This “Big Data” is so large and complex that traditional data processing applications are not up to the task. Challenges arise in collection, analysis, mining, sharing, transfer, visualization, archiving, and integration of these data. In this Special Issue, there is a focus on the systems-level analysis of Omics data, recent developments in gene ontology annotation, and advances in biological pathways and network biology. The integration of Omics data with clinical and biomedical data using machine learning is explored. This Special Issue covers new methodologies in the context of gene–environment interactions, tissue-specific gene expression, and how external factors or host genetics impact the microbiome.
Author : Ashis Sengupta
Publisher : World Scientific
ISBN 13 : 9812838236
Total Pages : 492 pages
Book Rating : 4.8/5 (128 download)
Download or read book Advances in Multivariate Statistical Methods written by Ashis Sengupta and published by World Scientific. This book was released on 2009 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printbegrænsninger: Der kan printes 10 sider ad gangen og max. 40 sider pr. session
