The phylogenomic revolution and its conceptual innovations: a text mining approach

Abstract

Natural language processing provides a quantitative framework with which to explore human cultural dynamics. Although this approach is less commonly used in the natural sciences, the text employed in scientific publications preserves a historical record of the development of disciplines as they evolve and mature. A high-throughput text mining study was performed here to investigate patterns of word use in publications dealing with phylogenomics. Over 2000 research articles in the field were surveyed, revealing the words whose frequency of use has shown the strongest positive correlation with time. Notably, concepts such as gene tree discordance and the susceptibility and discriminatory power of phylogenomic datasets were found to be among the strongest trending topics in the field. As systematics transitioned into a big data science, such obstacles to phylogenetic reconstruction were not left behind. On the contrary, phylogenomics opened a new door to explore these phenomena and their biological significance, becoming the focus of new theoretical and practical developments.