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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.
List of contents
Introduction. Data. Clustering Forms. Partitional Algorithms. Cluster Sampling Algorithms. Hierarchical Algorithms. Hybrid Algorithms. Asymmetry. Ambiguity. Validation. Large Scale and Parallel Algorithms. Appendices. Bibliography.
About the author
John D. MacCuish is the founder and president of Mesa Analytics & Computing, Inc. He has co-authored several software patents and has worked on many image processing, data mining, and statistical modeling applications, including IRS fraud detection, credit card fraud detection, and automated reasoning systems for drug discovery.
Norah E. MacCuish is the chief science officer of Mesa Analytics & Computing, Inc., where she acts as a consultant in the areas of drug design and compound acquisition and as a developer of commercial chemical information software products. She earned her Ph.D. in theoretical physical chemistry from Cornell University.
