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Next-Generation Sequencing Data Analysis

2016-04-06 Mathematics
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Release : 2016-04-06
Genre : Mathematics
Kind : eBook
Book Rating : 899/5 ( reviews)

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Book Synopsis Next-Generation Sequencing Data Analysis by : Xinkun Wang

Download or read book Next-Generation Sequencing Data Analysis written by Xinkun Wang. This book was released on 2016-04-06. Available in PDF, EPUB and Kindle. Book excerpt: A Practical Guide to the Highly Dynamic Area of Massively Parallel SequencingThe development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphi

Next-Generation Sequencing and Sequence Data Analysis

2015-11-04 Science
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Release : 2015-11-04
Genre : Science
Kind : eBook
Book Rating : 923/5 ( reviews)

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Book Synopsis Next-Generation Sequencing and Sequence Data Analysis by : Kuo Ping Chiu

Download or read book Next-Generation Sequencing and Sequence Data Analysis written by Kuo Ping Chiu. This book was released on 2015-11-04. Available in PDF, EPUB and Kindle. Book excerpt: Nucleic acid sequencing techniques have enabled researchers to determine the exact order of base pairs - and by extension, the information present - in the genome of living organisms. Consequently, our understanding of this information and its link to genetic expression at molecular and cellular levels has lead to rapid advances in biology, genetics, biotechnology and medicine. Next-Generation Sequencing and Sequence Data Analysis is a brief primer on DNA sequencing techniques and methods used to analyze sequence data. Readers will learn about recent concepts and methods in genomics such as sequence library preparation, cluster generation for PCR technologies, PED sequencing, genome assembly, exome sequencing, transcriptomics and more. This book serves as a textbook for students undertaking courses in bioinformatics and laboratory methods in applied biology. General readers interested in learning about DNA sequencing techniques may also benefit from the simple format of information presented in the book.

Statistical Analysis of Next Generation Sequencing Data

2014-07-03 Medical
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Release : 2014-07-03
Genre : Medical
Kind : eBook
Book Rating : 129/5 ( reviews)

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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. This book was released on 2014-07-03. 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.

Next Generation Sequencing and Data Analysis

2021-05-04 Science
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Release : 2021-05-04
Genre : Science
Kind : eBook
Book Rating : 900/5 ( reviews)

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Book Synopsis Next Generation Sequencing and Data Analysis by : Melanie Kappelmann-Fenzl

Download or read book Next Generation Sequencing and Data Analysis written by Melanie Kappelmann-Fenzl. This book was released on 2021-05-04. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides step-by-step protocols and detailed explanations for RNA Sequencing, ChIP-Sequencing and Epigenetic Sequencing applications. The reader learns how to perform Next Generation Sequencing data analysis, how to interpret and visualize the data, and acquires knowledge on the statistical background of the used software tools. Written for biomedical scientists and medical students, this textbook enables the end user to perform and comprehend various Next Generation Sequencing applications and their analytics without prior understanding in bioinformatics or computer sciences.

Algorithms for Next-Generation Sequencing Data

2017-09-18 Computers
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Release : 2017-09-18
Genre : Computers
Kind : eBook
Book Rating : 260/5 ( reviews)

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Book Synopsis Algorithms for Next-Generation Sequencing Data by : Mourad Elloumi

Download or read book Algorithms for Next-Generation Sequencing Data written by Mourad Elloumi. This book was released on 2017-09-18. Available in PDF, EPUB and Kindle. Book excerpt: The 14 contributed chapters in this book survey the most recent developments in high-performance algorithms for NGS data, offering fundamental insights and technical information specifically on indexing, compression and storage; error correction; alignment; and assembly. The book will be of value to researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences.

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