Microbial networks are an increasingly popular tool to investigate microbial community
structure, as they integrate multiple types of information and may represent systems-level …

Community detection in networks is one of the most popular topics of modern network
science. Communities, or clusters, are usually groups of vertices having higher probability of …

The modern science of networks has made significant advancement in the modeling of
complex real-world systems. One of the most important features in these networks is the …

The development of new technologies for map** structural and functional brain
connectivity has led to the creation of comprehensive network maps of neuronal circuits and …

Networks (or graphs) appear as dominant structures in diverse domains, including
sociology, biology, neuroscience and computer science. In most of the aforementioned …

This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …

The modern science of networks has brought significant advances to our understanding of
complex systems. One of the most relevant features of graphs representing real systems is …

Complex functional brain networks are large networks of brain regions and functional brain
connections. Statistical characterizations of these networks aim to quantify global and local …

Most methods proposed to uncover communities in complex networks rely on combinatorial
graph properties. Usually an edge-counting quality function, such as modularity, is optimized …