Includes bibliographical references and index.

(Publisher-supplied data) Introduction -- Data -- Clustering Forms -- Partitional Algorithms -- Cluster Sampling Algorithms - Hierarchical Algorithms -- Hybrid Algorithms -- Asymmetry -- Ambiguity -- Validation -- Large Scale and Parallel Algorithms.

"This book presents an introduction to cluster analysis and algorithms in the context of drug discovery clustering applications. It provides the key to understanding applications in clustering large combinatorial libraries (in the millions of compounds) for compound acquisition, HTS results, 3D lead hopping, gene expression for toxicity studies, and protein reaction data. Bringing together common and emerging methods, the text covers topics peculiar to drug discovery data, such as asymmetric measures and asymmetric clustering algorithms as well as clustering ambiguity and its relation to fuzzy clustering and overlapping clustering algorithms"--Provided by publisher.