  We overview networks which characterise dynamics in cellular automata. These
networks are derived from one-dimensional cellular automaton rules and global
states of the automaton evolution: de Bruijn diagrams, subsystem diagrams,
basins of attraction, and jump-graphs. These networks are used to understand
properties of spatially-extended dynamical systems: emergence of non-trivial
patterns, self-organisation, reversibility and chaos. Particular attention is
paid to networks determined by travelling self-localisations, or gliders.
