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Statistical Analysis Of Next Generation Sequencing Data

Author: Somnath Datta
Publisher: Springer
ISBN: 3319072129
Size: 57.63 MB
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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.

Encyclopedia Of Bioinformatics And Computational Biology

Publisher: Elsevier
ISBN: 0128114320
Size: 15.53 MB
Format: PDF, ePub
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Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics 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

Systems Immunology

Author: Jayajit Das
Publisher: CRC Press
ISBN: 1498717411
Size: 21.11 MB
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"Taken together, the body of information contained in this book provides readers with a bird’s-eye view of different aspects of exciting work at the convergence of disciplines that will ultimately lead to a future where we understand how immunity is regulated, and how we can harness this knowledge toward practical ends that reduce human suffering. I commend the editors for putting this volume together." –Arup K. Chakraborty, Robert T. Haslam Professor of Chemical Engineering, and Professor of Physics, Chemistry, and Biological Engineering, Massachusetts Institute of Technology, Cambridge, USA New experimental techniques in immunology have produced large and complex data sets that require quantitative modeling for analysis. This book provides a complete overview of computational immunology, from basic concepts to mathematical modeling at the single molecule, cellular, organism, and population levels. It showcases modern mechanistic models and their use in making predictions, designing experiments, and elucidating underlying biochemical processes. It begins with an introduction to data analysis, approximations, and assumptions used in model building. Core chapters address models and methods for studying immune responses, with fundamental concepts clearly defined. Readers from immunology, quantitative biology, and applied physics will benefit from the following: Fundamental principles of computational immunology and modern quantitative methods for studying immune response at the single molecule, cellular, organism, and population levels. An overview of basic concepts in modeling and data analysis. Coverage of topics where mechanistic modeling has contributed substantially to current understanding. Discussion of genetic diversity of the immune system, cell signaling in the immune system, immune response at the cell population scale, and ecology of host-pathogen interactions.

Immune System Modeling And Analysis

Author: Ramit Mehr
Publisher: Frontiers Media SA
ISBN: 2889195015
Size: 27.54 MB
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The rapid development of new methods for immunological data collection – from multicolor flow cytometry, through single-cell imaging, to deep sequencing – presents us now, for the first time, with the ability to analyze and compare large amounts of immunological data in health, aging and disease. The exponential growth of these datasets, however, challenges the theoretical immunology community to develop methods for data organization and analysis. Furthermore, the need to test hypotheses regarding immune function, and generate predictions regarding the outcomes of medical interventions, necessitates the development of mathematical and computational models covering processes on multiple scales, from the genetic and molecular to the cellular and system scales. The last few decades have seen the development of methods for presentation and analysis of clonal repertoires (those of T and B lymphocytes) and phenotypic (surface-marker based) repertoires of all lymphocyte types, and for modeling the intricate network of molecular and cellular interactions within the immune systems. This e-Book, which has first appeared as a ‘Frontiers in Immunology’ research topic, provides a comprehensive, online, open access snapshot of the current state of the art on immune system modeling and analysis.

The Least Cost Path From Landscape Genetics To Landscape Genomics

Author: Samuel A. Cushman
Publisher: Frontiers Media SA
ISBN: 2889455483
Size: 32.43 MB
Format: PDF, Kindle
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Ecosystems are the stage on which the play of evolution is acted, and ecosystems are complex, spatially structured and temporally varying. The purpose of this Research Topic is to explore critical challenges and opportunities for the transition from landscape genetics to landscape genomics. Landscape genetics has focused on the spatial analysis of small genetic datasets, typically comprised of less than 20 microsatellite markers, taken from clusters of individuals in putative populations or distributed individuals across landscapes. The recent emergence of large scale genomic datasets produced by next generation sequencing methods poses tremendous challenge and opportunity to the field. Perhaps the greatest is to produce, process, curate, archive and analyze spatially referenced genomic datasets in a way such that research is led by a priori hypotheses regarding how environmental heterogeneity and temporal dynamics interact to affect gene flow and selection. The papers in the Research Topic cover a broad range of topics under this area of focus, from reviews of the emergence of landscape genetics, to best practices in spatial analysis of genetic data. The compilation, like the emerging field itself, is eclectic and illustrates the scope of both the challenges and opportunities of this emerging field.