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The State of the Art in Transcriptome Analysis RNA 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 levels and to discover novel genes, transcripts, and whole transcriptomes.
Balanced Coverage of Theory and Practice.Each chapter starts with theoretical background, followed by descriptions of relevant analysis tools and practical examples. Accessible to both bioinformaticians and nonprogramming wet lab scientists, the examples illustrate the use of command-line tools, R, and other open source tools, such as the graphical Chipster software.
The Tools and Methods to Get Started in Your Lab.
The State of the Art in Transcriptome Analysis RNA 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
This bestseller is known for its modern, practical approach to regression-analysis methods that students will find applicable to real-life problems. APPLIED REGRESSION ANALYSIS AND MULTIVARIABLE METHODS highlights the role of the computer in contemporary statistics with numerous printouts and
A practical guide to data-intensive humanities research using the Python programming languageThe use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials
Balancing theoretical foundations with practical strategies, this book helps you develop an approach to your qualitative analysis that is both systematic and insightful. It demonstrates the importance of tying analysis into every aspect of research, from design, through data collection and
Compact data structures help represent data in reduced space while allowing it to be queried, navigated, and operated in compressed form. They are essential tools for efficiently handling massive amounts of data by exploiting the memory hierarchy. They also reduce the resources needed in
Rachel Ritterbusch's Practical Approaches to Teaching Film is a collection of essays focusing on the use of film in settings ranging from an introductory film class to an upper-division Women's Studies course. Drawing on their experience in the classroom, contributors to this anthology show how
Practical guidance for wildlife professionals working to improve study design, data analysis, and the application of results to habitat and population management.Winner of the Wildlife Society Publications Book Award by The Wildlife SocietyDespite major advances in sampling techniques and
Optimal Mean Reversion Trading: Mathematical Analysis and Practical Applications provides a systematic study to the practical problem of optimal trading in the presence of mean-reverting price dynamics. It is self-contained and organized in its presentation, and provides rigorous mathematical
Big data, genomics, and quantitative approaches to network-based analysis are combining to advance the frontiers of medicine as never before. Network Medicine introduces this rapidly evolving field of medical research, which promises to revolutionize the diagnosis and treatment of human diseases
A practical and up-to-date guide to pacemaker technology and its clinical implementation As the field of cardiology continues to advance and expand, so too does the technology and expertise behind today's electrophysiological devices. Cardiac Pacing, Defibrillation and Resynchronization has been
This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science,
Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian
See How Graphics Reveal InformationGraphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages
Why does the World Need--Excel Data Analysis, Modeling, and Simulation? When spreadsheets ?rst became widely available in the early 1980s, it spawned a revolution in teaching. What previously could only be done with arcane software and large scale computing was now available to the common-man, on a
A clear and thorough introduction to meta-analysis, the process of synthesizing data from a series of separate studies. The first edition of this text was widely acclaimed for the clarity of the presentation, and quickly established itself as the definitive text in this field. The fully updated
A straightforward, practical guide for doing Ericksonian
A practical approach to business transformation Fit for Growth* is a unique approach to business transformation that explicitly connects growth strategy with cost management and organization restructuring. Drawing on 70-plus years of strategy consulting experience and in-depth research, the experts
Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work with small-area spatial and spatial-temporal data. It assumes a grounding in statistical theory up to the standard linear
This new edition of this bestselling guide offers an integrated approach to process improvement that delivers quick and substantial results in quality and productivity in diverse settings. The authors explore their Model for Improvement that worked with international improvement efforts at
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the