Using a collaborative and interdisciplinary author base with experience in the pharmaceutical industry and academia, this book is a practical resource for high content (HC) techniques. • Instructs readers on the fundamentals of high content screening (HCS) techniques • Focuses on practical and widely-used techniques like image processing and multiparametric assays • Breaks down HCS into individual modules for training and connects them at the end • Includes a tutorial chapter that works through sample HCS assays, glossary, and detailed appendices

The Second Edition of Content Analysis: An Introduction to Its Methodology is a definitive sourcebook of the history and core principles of content analysis as well as an essential resource for present and future studies. The book introduces readers to ways of analyzing meaningful matter such as texts, images, voices - that is, data whose physical manifestations are secondary to the meanings that a particular population of people brings to them. Organized into three parts, the book examines the conceptual and methodological aspects of content analysis and also traces several paths through content analysis protocols. The author has completely revised and updated the Second Edition, integrating new information on computer-aided text analysis. The book also includes a practical guide that incorporates experiences in teaching and how to advise academic and commercial researchers. In addition, Krippendorff clarifies the epistemology and logic of content analysis as well as the methods for achieving its aims. Intended as a textbook for advanced undergraduate and graduate students across the social sciences, Content Analysis, Second Edition will also be a valuable resource for practitioners in a variety of disciplines.

As the use of high-throughput screening expands and creates more interest in the academic community, the need for detailed reference materials becomes ever more pressing. Cell-Based Assays for High-Throughput Screening: Methods and Protocols aims to fill an important part of this need by providing an easily accessible reference volume for cell-based phenotypic screening. Leading researchers in the field contribute state-of-the-art methods with actionable protocols covering four major areas of study: model biological systems, screening modalities and assay systems, detection technologies, and approaches to data analysis. Written in the highly successful Methods in Molecular BiologyTM series format, each chapter includes a brief introduction to the subject, lists of necessary materials and reagents, step-by-step laboratory protocols, and a Notes section detailing tips on troubleshooting and avoiding known pitfalls. Cutting-edge and easy-to-use, Cell-Based Assays for High-Throughput Screening: Methods and Protocols presents an overview of relevant approaches, enabling the direct application of existing methods to new discoveries while also inspiring researchers to approach their screening projects in a conceptually modular fashion, enhancing the power to discover through new combinations of existing approaches.

This concise, self-contained and cohesive book focuses on commonly used and recently developed methods for designing and analyzing high-throughput screening (HTS) experiments from a statistically sound basis. Combining ideas from biology, computing and statistics, the author explains experimental designs and analytic methods that are amenable to rigorous analysis and interpretation of RNAi HTS experiments. The opening chapters are carefully presented to be accessible both to biologists with training only in basic statistics and to computational scientists and statisticians with basic biological knowledge. Biologists will see how new experiment designs and rudimentary data-handling strategies for RNAi HTS experiments can improve their results, whereas analysts will learn how to apply recently developed statistical methods to interpret HTS experiments.

There has always been some tension between proponents of hypothesis-driven and discovery-driven research in the broad field of life sciences. Academic research has been primarily focused on hypothesis-driven research. However, the success of the human genome project, a discovery-driven research approach, has opened the door to adding other types of discovery-driven research to a continuum of research approaches. In contrast, drug discovery research in the pharmaceutical industry has embraced discovery-driven research for many years. A good example has been the discovery of active compounds from large chemical libraries, through screening campaigns. The success of the human genome project has also demonstrated the need for both academic researchers and industrial researchers to now understand the functions of genes and gene products. The cell is the basic unit of life and it has been at the cellular level where function can be demonstrated most cost-effectively and rapidly. High content screening (HCS) was developed by Cellomics Inc. in the mid-1990s to address the need for a platform that could be used in the discovery-driven research and development required to understand the functions of genes and gene products at the level of the cell.

The authoritative reference on High Content Screening (HCS) in biological and pharmaceutical research, this guide covers: the basics of HCS: examples of HCS used in biological applications and early drug discovery, emphasizing oncology and neuroscience; the use of HCS across the drug development pipeline; and data management, data analysis, and systems biology, with guidelines for using large datasets. With an accompanying CD-ROM, this is the premier reference on HCS for researchers, lab managers, and graduate students.

Qualitative content analysis is a powerful method for analyzing large amounts of qualitative data collected through interviews or focus groups. It is frequently employed by students, but introductory textbooks on content analysis have largely focused on the quantitative version of the method. In one of the first to focus on qualitative content analysis, Margrit Schreier takes students step-by step through: - creating a coding frame - segmenting the material - trying out the coding frame - evaluating the trial coding - carrying out the main coding - what comes after qualitative content analysis - making use of software when conducting qualitative content analysis. Each part of the process is described in detail and research examples are provided to illustrate each step. Frequently asked questions are answered, the most important points are summarized, and end of chapter questions provide an opportunity to revise these points. After reading the book, students are fully equiped to conduct their own qualitative content analysis. Designed for upper level undergraduate, MA, PhD students and researchers across the social sciences, this is essential reading for all those who want to use qualitative content analysis.

This landmark text from world-leading radiologist describes and illustrates how imaging techniques are created, analyzed and applied to biomedical problems.

This research reference introduces readers to the data mining technologies available for use in content analysis research. Supporting the increasingly popular trend of employing digital analysis methodologies in the humanities, arts, and social sciences, this work provides crucial answers for researchers who are not familiar with data mining approaches and who do not know what they can do, how they work, or how their strengths and weaknesses match up to the strengths and weaknesses of human coded content analysis data. Offering valuable insights and guidance for using automated analytical techniques in content analysis research, this guide will appeal to both novice and experienced researchers throughout the humanities, arts, and social sciences.

Biological and chemical sciences have undergone an unprecedented transformation, reflected by the huge use of parallel and automated technologies in key fields such as genome sequencing, DNA chips, nanoscale functional biology or combinatorial chemistry. It is now possible to generate and store from tens of thousands to millions of new small molecules, based on enhanced chemical synthesis strategies. Automated screening of small molecules is one of the technologies that has revolutionized biology, first developed for the pharmaceutical industry and recently introduced in academic laboratories. High-throughput and high-content screening allow the identification of bioactive compounds in collections of molecules (chemical libraries), being effective on biological targets defined at various organisational scales, from proteins to cells to complete organisms. These bioactive molecules can be therapeutic drug candidates, molecules for biotech, diagnostic or agronomic applications, or tools for basic research. Handling a large number of biological (genomic and post-genomic), chemical and experimental information, screening approaches cannot be envisaged without any electronic storage and mathematical treatment of the data. “Chemogenomics and Chemical Genetics” is an introductory manual presenting methods and concepts making up the basis for this recent discipline. This book is dedicated to biologists, chemists and computer scientist beginners. It is organized in brief, illustrated chapters with practical examples. Clear definitions of biological, chemical and IT concepts are given in a glossary section to help readers who are not familiar with one of these disciplines. "Chemogenomics and Chemical Genetics" should therefore be helpful for students (from Bachelor's degree level), technological platform engineers, and researchers in biology, chemistry, bioinformatics, cheminformatics, both in biotech and academic laboratories.