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This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data.
Written by a high-profile international author and editor team, this handbook and ready reference presents a combination of statistical, information-theoretic, and data analysis methods for designing empirical models involving molecular descriptors within bioinformatics.
This latest volume in the successful Network Biology series presents current methods for determining the entropy of networks, covering the analysis of mathematical properties of methods as well as applications in areas ranging from applied mathematics to chemical graph theory.
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