  Change is a fundamental ingredient of interaction patterns in biology,
technology, the economy, and science itself: Interactions within and between
organisms change; transportation patterns by air, land, and sea all change; the
global financial flow changes; and the frontiers of scientific research change.
Networks and clustering methods have become important tools to comprehend
instances of these large-scale structures, but without methods to distinguish
between real trends and noisy data, these approaches are not useful for
studying how networks change. Only if we can assign significance to the
partitioning of single networks can we distinguish meaningful structural
changes from random fluctuations. Here we show that bootstrap resampling
accompanied by significance clustering provides a solution to this problem. To
connect changing structures with the changing function of networks, we
highlight and summarize the significant structural changes with alluvial
diagrams and realize de Solla Price's vision of mapping change in science:
studying the citation pattern between about 7000 scientific journals over the
past decade, we find that neuroscience has transformed from an
interdisciplinary specialty to a mature and stand-alone discipline.
