This volume presents a collection of papers dealing with various aspects of clustering in biological networks and other related problems in computational biology. It consists of two parts, with the first part containing surveys of selected topics and the second part presenting original research contributions. This book will be a valuable source of material to faculty, students, and researchers in mathematical programming, data analysis and data mining, as well as people working in bioinformatics, computer science, engineering, and applied mathematics. In addition, the book can be used as a supplement to any course in data mining or computational/systems biology.
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This text offers introductory knowledge of a wide range of clustering and other quantitative techniques used to solve biological problems. It provides a detailed overview of the practical aspects of real-life biological problems, thus helping researchers identify current and future challenges or trends arising in the research areas concerning clustering problems in biological networks. With contributions from experts in diverse disciplines, readers will learn more about biology from massive data networks through quantitative methods such as clustering and classification. Aimed at senior-level students, investigators, and practitioners from the science, engineering, and medical domains, this book will help them share important concepts, ideas, and scientific methodology in order to boost the knowledge of this relatively new and exciting topic.
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