Post-Transcriptional Gene Regulation (Methods in Molecular Biology)

Post-Transcriptional Gene Regulation (Methods in Molecular Biology) Review

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Post-Transcriptional Gene Regulation (Methods in Molecular Biology) Feature

This volume strives to present current technical approaches to most aspects of post-transcriptional control and provide the reader with a useful and versatile laboratory bench resource. With chapters split into sections covering bioinformatics, fundamental aspects of the study of RNA biology, and techniques for specific aspects of RNA biology, the expert authors have filled the book with invaluable tricks of the trade, perfected in their laboratories.

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Molecular Biology of the SARS-Coronavirus

Molecular Biology of the SARS-Coronavirus Review

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Molecular Biology of the SARS-Coronavirus Feature

The SARS outbreak in 2002 caused unprecedented devastation and exhibited unusually high rates of morbidity and mortality. For the SARS coronavirus, the transmission vehicle was man. What added to the spread was man’s convenient, rapid and affordable ways of travel that caused the virus to spread globally in a short span of time. The SARS coronavirus jumped the species barrier, similar to many recent zoonotic diseases – avian flu, swine flu, Nipah and encephalitis virus. It is extremely important for us to understand the enemy before it strikes again in order to be able to combat such outbreaks as and when they occur. Molecular mechanisms that the virus exploits within its host and that result in infection and pathogenesis are the key to being able to block its transmission cycle. In this book, leading scientists from around the globe have discussed molecular aspects of viral entry, replication, viral gene expression, pathogenesis and host immune response against the SARS coronavirus.

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Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)

Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health) Review

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Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health) Feature

Full four-color book.

Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R.

All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies.

Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

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DNA Methylation: Methods and Protocols (Methods in Molecular Biology)

DNA Methylation: Methods and Protocols (Methods in Molecular Biology) Review

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DNA Methylation: Methods and Protocols (Methods in Molecular Biology) Feature

Over the past few years, DNA methylation technologies and our knowledge of DNA methylation patterns have been advancing at a breathtaking pace. Due to this fact, DNA Methylation: Methods and Protocols, Second Edition completely revises, updates, and expands upon the popular first edition with the most current novel techniques, easier to use and more refined by the tested experience of leading experts. This revision reflects contemporary study of the subject: the analysis of gene-specific DNA methylation patterns has been complemented by genome-wide approaches, and epigenomics takes a central place. Written in the highly successful Methods in Molecular Biology™ series format, the chapters in this volume present brief introductions to the topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and notes which highlight tips on troubleshooting and avoiding known pitfalls. Comprehensive and cutting-edge, DNA Methylation: Methods and Protocols, Second Edition is the perfect resource for scientists who wish to further our understanding of the molecular processes that determine the genomic DNA methylation landscape and for those who aim to identify and implement DNA methylation-based biomarkers for clinical and diagnostic applications.

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The Statistical Analysis of Recurrent Events (Statistics for Biology and Health)

The Statistical Analysis of Recurrent Events (Statistics for Biology and Health) Review

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The Statistical Analysis of Recurrent Events (Statistics for Biology and Health) Feature

This book presents models and statistical methods for the analysis of recurrent event data. The authors provide broad, detailed coverage of the major approaches to analysis, while emphasizing the modeling assumptions that they are based on. More general intensity-based models are also considered, as well as simpler models that focus on rate or mean functions. Parametric, nonparametric and semiparametric methodologies are all covered, with procedures for estimation, testing and model checking.

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Survival and Event History Analysis: A Process Point of View (Statistics for Biology and Health)

Survival and Event History Analysis: A Process Point of View (Statistics for Biology and Health) Review

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Survival and Event History Analysis: A Process Point of View (Statistics for Biology and Health) Feature

The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics.

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