<b>Graphs and Networks</b> <p><b>A unique blend of graph theory and network science for mathematicians and data science professionals alike.</b> <p>Featuring topics such as minors, connectomes, trees, distance, spectral graph theory, similarity, centrality, small-world networks, scale-free networks, graph algorithms, Eulerian circuits, Hamiltonian cycles, coloring, higher connectivity, planar graphs, flows, matchings, and coverings, Graphs and Networks contains modern applications for graph theorists and a host of useful theorems for network scientists. <p>The book begins with applications to biology and the social and political sciences and gradually takes a more theoretical direction toward graph structure theory and combinatorial optimization. A background in linear algebra, probability, and statistics provides the proper frame of reference. <p>Graphs and Networks also features: <ul><li>Applications to neuroscience, climate science, and the social and political sciences</li> <li>A research outlook integrated directly into the narrative with ideas for students interested in pursuing research projects at all levels</li> <li>A large selection of primary and secondary sources for further reading</li> <li>Historical notes that hint at the passion and excitement behind the discoveries</li> <li>Practice problems that reinforce the concepts and encourage further investigation and independent work</li></ul>
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