High Content Screening by D. Lansing Taylor , Springer

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Springer High Content Screening by D. Lansing Taylor

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._x000D_ _x000D_Part I. Introduction to High Content Screening_x000D_ _x000D_ Past, Present, and Future of High Content Screening and the Field of Cellomics_x000D_ D. Lansing Taylor_x000D_ _x000D_ A Pharmaceutical Company Users Perspective on the Potential of High Content Screening in Drug Discovery_x000D_ Ann F. Hoffman and Ralph J. Garippa_x000D_ _x000D_ Linking Microscopy and High Content Screening in Large-Scale Biomedical Research_x000D_ James G. Evans and Paul Matsudaira._x000D_ _x000D_ Part II. Instrumentation, Biological Application Software, and Sample Preparation_x000D_ _x000D_ Requirements, Features, and Performance of High Content Screening Platforms_x000D_ Albert H. Gough and Paul A. Johnston_x000D_ _x000D_ Characteristics and Value of Directed Algorithms in High Content Screening_x000D_ Richik N. Ghosh, Oleg Lapets, and Jeffrey R. Haskins_x000D_ _x000D_ Characteristics and Value of Machine Learning for Imaging in High Content Screening_x000D_ Juergen A. Klenk_x000D_ _x000D_ Tools for Quantitative and Validated Measurements of Cells_x000D_ Anne L. Plant, John T. Elliott, Alessandro Tona, Dennis McDaniel, and Kurt J. Langenbach_x000D_ _x000D_ Automated Cell Plating and Sample Treatments for Fixed Cells in High Content Assays_x000D_ Gillian R. Richards, Julie E. Kerby, Grace K. Y. Chan, and Peter B. Simpson_x000D_ _x000D_ Differentiating Primary Human Cells in Rapid-Throughput Discovery Applications_x000D_ Daniel R. Marshak and Dale E. Greenwalt_x000D_ _x000D_ Use of the CellCard (TM) System for Analyzing Multiple Cell Types in Parallel_x000D_ Oren Beske, Daniel Bassoni, and Simon Goldbard_x000D_ _x000D_ Part III. Reagents_x000D_ _x000D_ Reagents to Measure and Manipulate Cell Functions_x000D_ Kenneth A. Giuliano, D. Lansing Taylor, and Alan S. Waggoner_x000D_ _x000D_ Fluorescent Proteins and Engineered Cell Lines_x000D_ Nick Thomas_x000D_ _x000D_ Optimizing the Integration of Immunoreagents and Fluorescent Probes for Multiplexed High Content Screening Assays_x000D_ Kenneth A. Giuliano_x000D_ _x000D_ The HaloTag (TM): A Novel Technology for Cell Imaging andProtein Analysis_x000D_ Georgyi V. Los and Keith Wood_x000D_ _x000D_ Protein Labeling With FlAsH and ReAsH_x000D_ Thomas Machleidt, Matt Robers, and George T. Hanson_x000D_ _x000D_ Exploiting Network Biology to Improve Drug Discovery_x000D_ Marnie L. MacDonald and John K. Westwick_x000D_ _x000D_ Physiological Indicators of Cell Function_x000D_ Michael J. Ignatius and Jeffrey T. Hung_x000D_ _x000D_ The Use of siRNA to Validate Immunofluorescence Studies_x000D_ K. Gregory Moore, Wayne Speckmann, and Ronald P. Herzig_x000D_ _x000D_ Caged Substrates Applied to High Content Screening: An Introduction With an Eye to the Future_x000D_ Peter G. Conrad, II, Rajesh V. Chavli, and Richard S. Givens_x000D_ _x000D_ Part IV. Informatics and Bioinformatics_x000D_ _x000D_ Overview of Informatics for High Content Screening_x000D_ R. Terry Dunlay, Wallace J. Czekalski, and Mark A. Collins_x000D_ _x000D_ Large-Scale Data Management for High Content Screening_x000D_ Leon S. Garfinkel_x000D_ _x000D_ An Integrated Biomedical Knowledge Extraction and Analysis Platform: Using Federated Search and Document Clustering Technology_x000D_ Donald P. Taylor_x000D_ _x000D_ Visualization of High Content Screening Data_x000D_ Matthew J. Anstett_x000D_ _x000D_ Pathway Mapping Tools for Analysis of High Content Data_x000D_ Sean Ekins, Yuri Nikolsky, Andrej Bugrim, Eugene Kirillov, and Tatiana Nikolskaya_x000D_ _x000D_ Part V. Assays and Applications of High Content Screening_x000D_ _x000D_ Systems Biology in Cancer Research: Genomics to Cellomics_x000D_ Jackie L. Stilwell, Yinghui Guan, Richard M. Neve, and Joe W. Gray_x000D_ _x000D_ Target Validation in Drug Discovery_x000D_ Robert A. Blake_x000D_ _x000D_ High Content Screening as a Screening Tool in Drug Discovery_x000D_ Anthony Nichols_x000D_ _x000D_ Discovery of Protein Kinase Phosphatase Inhibitors_x000D_ Andreas Vogt and John S. Lazo_x000D_ _x000D_ High Content Translocation Assays for Pathway Profiling_x000D_ Frosty Loechel, Sara Bjorn, Viggo Linde, Morten Praestegaard, and Len Pagliaro_x000D_ _x000D_ In Vitro Cytotoxicity Assessment_x000D_ Peter_x000D_