  We analyzed Medical Subject Headings (MeSH) from 21.6 million research
articles indexed by PubMed to map this vast space of entities and their
relations, providing insights into the origins and future of biomedical
convergence. Detailed analysis of MeSH co-occurrence networks identifies three
robust knowledge clusters: the vast universe of microscopic biological entities
and structures; systems, disease and diagnostics; and emergent biological and
social phenomena underlying the complex problems driving the health, behavioral
and brain science frontiers. These domains integrated from the 1990s onward by
way of technological and informatic capabilities that introduced highly
controllable, scalable and permutable research processes and invaluable imaging
techniques for illuminating fundamental structure-function-behavior questions.
Article-level analysis confirms a positive relationship between team size and
topical diversity, and shows convergence to be increasing in prominence but
with recent saturation. Together, our results invite additional policy support
for cross-disciplinary team assembly to harness transdisciplinary convergence.
