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With a DVD of color figures, this book provides an expert guide to extracting the most pertinent information from pharmaceutical and biomedical data. It offers a concise overview of common and recent clustering methods used in bioinformatics and drug discovery. The authors cover the clustering of small and large data sets, parallelization of clustering algorithms, validation and visualization, asymmetric clustering, and clustering ambiguity. They provide many real-world examples from industrial settings, such as combinatorial library design and compound databases, and include exercises at the end of each chapter.
Presents an introduction to cluster analysis and algorithms in the context of drug discovery clustering applications. This book provides an understanding of the applications in clustering large combinatorial libraries for compound acquisition, HTS results, 3D lead hopping, gene expression for toxicity studies, and protein reaction data.
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