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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: Robert E. Farrell Jr. Publisher: Academic Press ISBN: 0080884954 Category : Science Languages : en Pages : 742
Book Description
This is the fourth edition of the successful laboratory guide which has translated the rich story of riboneucleic acid for over fifteen years. RNA Methodologies 4e presents the latest collection of tested laboratory protocols for the isolation and characterization of eukaryotic and prokaryotic RNA with greater emphasis on transcript profiling, including quantification issues and elucidation of alternative transcription start sites. Collectively the chapters work together providing analysis with clear take-home lessons to assist researchers to understand RNA and to optimize time at the bench. The abundant use of flow charts, tables and graphs are especially helpful in the planning and implementation phases of a project and facilitate learning. 30% new material in this edition includes the addition of RNA isolation protocols including RNA isolation from tissue, expansion of PCR optimization analysis and RNA interference sections, the introduction of a new chapter dealing with the molecular biology of plants, and an expanded glossary. 30% new material with the addition of RNA isolation protocols including RNA isolation from tissue, expansion of PCR optimization analysis and RNA interference sections, the introduction of a new chapter dealing with the molecular biology of plants, and an expanded glossary Author is a well-recognized expert in the field of RNA experimentation and founded Exon-Intron, a well-known biotechnology educational workshop center Includes classic and contemporary techniques useful for all labs
Author: Serghei Mangul Publisher: Springer ISBN: 3030139735 Category : Computers Languages : en Pages : 93
Book Description
Advances in RNA-sequencing (RNA-seq) technologies have provided an unprecedented opportunity to explore the gene expression landscape across individuals, tissues, and environments by efficiently profiling the RNA sequences present in the samples. When a reference genome sequence or a transcriptome of the sample is available, mapping-based RNA-seq analysis protocols align the RNA-seq reads to the reference sequences, identify novel transcripts, and quantify the abundance of expressed transcripts.The reads that fail to map to the human reference, known as unmapped reads, are a large and often overlooked output of standard RNA-seq analyses. Even in carefully executed experiments, the unmapped reads can comprise a considerable fraction of the complete set of reads produced, and can arise due to technical sequencing produced by low-quality and error-prone copies of the nascent RNA sequence being sampled. Reads can also remain unmapped due to unknown transcripts, recombined B and T cell receptor sequences, A-to-G mismatches from A-to-I RNA editing, trans-splicing, gene fusion, circular RNAs, and the presence of non-host RNA sequences (e.g. bacterial, fungal, and viral organisms). Unmapped reads represent a rich resource for the study of B and T cell receptor repertoires and the human microbiome system—without incurring the expense of additional targeted sequencing.This book introduces and describes the Read Origin Protocol (ROP), a tool that identifies the origin of both mapped and unmapped reads. The protocol first identifies human reads using a standard high-throughput algorithm to map them onto a reference genome and transcriptome. After alignment, reads are grouped into genomic (e.g. CDS, UTRs, introns) and repetitive (e.g. SINEs, LINEs, LTRs) categories. The rest of the ROP protocol characterizes the remaining unmapped reads, which failed to map to the human reference sequences.
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: Hailing Jin
Author: Hailing Jin
Author: Elijah Joshua
Author: Vera Pawlowsky-Glahn
Author: Filippo Geraci
Author: Eija Korpelainen
Author: Robert E. Farrell Jr.
Author: Serghei Mangul
Author: Jacquie T. Keer
Author: David J. Balding
Author: Somnath Datta