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, assortative networks, covert 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 untapped 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