Understanding changes and trends in biomedical knowledge is crucial for individuals, groups, and institutions as biomedicine improves people’s lives, supports national economies, and facilitates innovation. However, as knowledge changes what evidence illustrates knowledge changes? In the case of microbiome, a multi-dimensional concept from biomedicine, there are significant increases in publications, citations, funding, collaborations, and other explanatory variables or contextual factors. What is observed in the microbiome, or any historical evolution of a scientific field or scientific knowledge, is that these changes are related to changes in knowledge, but what is not understood is how to measure and track changes in knowledge. This investigation highlights how contextual factors from the language and social context of the microbiome are related to changes in the usage, meaning, and scientific knowledge on the microbiome. Two interconnected studies integrating qualitative and quantitative evidence examine the variation and change of the microbiome evidence are presented. First, the concepts microbiome, metagenome, and metabolome are compared to determine the boundaries of the microbiome concept in relation to other concepts where the conceptual boundaries have been cited as overlapping. A collection of publications for each concept or corpus is presented, with a focus on how to create, collect, curate, and analyze large data collections. This study concludes with suggestions on how to analyze biomedical concepts using a hybrid approach that combines results from the larger language context and individual words. Second, the results of a systematic review that describes the variation and change of microbiome research, funding, and knowledge are examined. A corpus of approximately 28,000 articles on the microbiome are characterized, and a spectrum of microbiome interpretations are suggested based on differences related to context. The collective results suggest the microbiome is a separate concept from the metagenome and metabolome, and the variation and change to the microbiome concept was influenced by contextual factors. These results provide insight into how concepts with extensive resources behave within biomedicine and suggest the microbiome is possibly representative of conceptual change or a preview of new dynamics within science that are expected in the future.

Studies in neocortical neurogenesis have experienced an explosive growth since the early 2000s, measured by the increasing number of publications each year. I examine here the influence of Arnold Kriegstein in the field using Topic Modeling, a set of algorithms that can be applied to a collection of texts to elucidate the central themes of said collection. Using a Java-based software called MALLET, I obtained data for his corpus, and compared it to the texts of other researchers in the field. This latter collection, which I dub "General Corpus", was separated by year from 2000 to 2014. I found that Kriegstein's most frequently discussed topic concerned highly unique terms such as GABA, glutamate, and receptor, which did not appear in any of the primary topics of the General Corpus. This was in contrast to my initial hypothesis that Kriegstein's importance stemmed from his examination of different phenomena that constitute the broader aspect of neocortical neurogenesis. I predicted that the terms in Kriegstein's primary topic would appear many times throughout the topics of the General Corpus, but it was not so, aside from the common ones such as neurons, cortical, and development. Taken in tandem with NIH Reporter data, these results suggest that Kriegstein obtains a large amount of research funding because his studies concern unique topics when compared to others in the field. The implications of these findings are especially relevant in a world where funding is becoming increasingly difficult to come by.