A unique blend of graph theory and network science for mathematicians and data science professionals alike.

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.

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.

Graphs and Networks also features:

• Applications to neuroscience, climate science, and the social and political sciences
• A research outlook integrated directly into the narrative with ideas for students interested in pursuing research projects at all levels
• A large selection of primary and secondary sources for further reading
• Historical notes that hint at the passion and excitement behind the discoveries
• Practice problems that reinforce the concepts and encourage further investigation and independent work