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Author: Hailing Jin Publisher: Humana Press ISBN: 9781493959167 Category : Medical Languages : en Pages : 248
Book Description
This book examines a wide range of techniques on RNA extraction, detection, quantification, visualization, and genome-wide profiling, from conventional methods to state-of-the-art high throughput approaches.
Author: Hailing Jin Publisher: Humana Press ISBN: 9781493959167 Category : Medical Languages : en Pages : 248
Book Description
This book examines a wide range of techniques on RNA extraction, detection, quantification, visualization, and genome-wide profiling, from conventional methods to state-of-the-art high throughput approaches.
Author: Elijah Joshua Publisher: Createspace Independent Publishing Platform ISBN: 9781548213190 Category : Languages : en Pages : 234
Book Description
RNA abundance analysis is one of the most important approaches for gene expression studies in the field of molecular biology. In RNA Abundance Analysis: Methods and Protocols, expert researchers cover a wide range of techniques on RNA extraction, detection, quantification, visualization, and genome-wide profiling, from conventional methods to state-of-the-art high throughput approaches. This volume includes detailed techniques to examine mRNAs, small non-coding RNAs, protein-associated small RNAs, sulfur-containing RNAs, viral and satellite RNAs, RNA isoforms, and alternatively spliced RNA variants from various organisms, as well as key discussions of computational data processing for genome-wide datasets.
Author: Vera Pawlowsky-Glahn Publisher: John Wiley & Sons ISBN: 0470711353 Category : Mathematics Languages : en Pages : 405
Book Description
It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.
Author: Eija Korpelainen Publisher: CRC Press ISBN: 1466595019 Category : Mathematics Languages : en Pages : 322
Book Description
The State of the Art in Transcriptome AnalysisRNA sequencing (RNA-seq) data offers unprecedented information about the transcriptome, but harnessing this information with bioinformatics tools is typically a bottleneck. RNA-seq Data Analysis: A Practical Approach enables researchers to examine differential expression at gene, exon, and transcript le
Author: Alessandro Cellerino Publisher: Springer ISBN: 8876426426 Category : Mathematics Languages : en Pages : 188
Book Description
The goal of this book is to be an accessible guide for undergraduate and graduate students to the new field of data-driven biology. Next-generation sequencing technologies have put genome-scale analysis of gene expression into the standard toolbox of experimental biologists. Yet, biological interpretation of high-dimensional data is made difficult by the lack of a common language between experimental and data scientists. By combining theory with practical examples of how specific tools were used to obtain novel insights in biology, particularly in the neurosciences, the book intends to teach students how to design, analyse, and extract biological knowledge from transcriptome sequencing experiments. Undergraduate and graduate students in biomedical and quantitative sciences will benefit from this text as well as academics untrained in the subject.
Author: David J. Balding Publisher: John Wiley & Sons ISBN: 1119429250 Category : Science Languages : en Pages : 1828
Book Description
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
Author: Somnath Datta Publisher: Springer ISBN: 3319072129 Category : Medical Languages : en Pages : 438
Book Description
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.
Author: Robert E. Farrell Jr. Publisher: Elsevier ISBN: 0323916562 Category : Science Languages : en Pages : 962
Book Description
RNA Methodologies: A Laboratory Guide for Isolation and Characterization, Sixth Edition provides the most up-to-date ribonucleic acid lab techniques for seasoned scientists and graduate students alike. This edition features new material on RNA sequencing, RNA in Situ Hybridization, non-coding RNAs, computational RNA biology, transcriptomes and bioinformatics, along with the latest advances in methods and protocols across the field of RNA investigation. As a leader in the field, Dr. Farrell provides a wealth of knowledge on the topic of RNA biology while also giving readers helpful hints and troubleshooting techniques from his own personal experience in this subject area. This book presents the essential knowledge and techniques to use when working with RNA for the experienced practitioner, while also aiding the beginner in fully understanding this important branch of molecular biology. Presents the latest information covering all aspects of working with RNA, delivering a holistic understanding of this leading field in molecular biology Builds from basic information on RNA techniques to in-depth protocols for specific applications Features new chapters on RNA sequencing and RNA in situ hybridization Includes new material on RNA clinical applications and innovations, including RNA therapeutics and RNA vaccines, with particular relevance to coronavirus Comprises the latest developments in transcriptomes and bioinformatics, with new material on computational RNA biology, RNA CHiP analysis, aptamer biology and RNA epigenetics
Author: Hailing Jin
Author: Hailing Jin
Author: Elijah Joshua
Author: Vera Pawlowsky-Glahn
Author: Filippo Geraci
Author: Eija Korpelainen
Author: Alessandro Cellerino
Author: David J. Balding
Author: Somnath Datta
Author: Robert E. Farrell Jr.
Author: Jacquie T. Keer