Many digital libraries, such as PubMed, Scopus, appeared with the growth of the Internet: thus, many scientific articles became available in the digital form. We got an opportunity to query articles metadata, gather statistics, build co-authorship graphs, etc. This includes estimating the authors/institutions activity, revealing their interactions and other properties. In this work we present the analysis of the characteristics of institutions interactions in the miRNA science field using the data from PubMed digital library. To tackle the problem of the institution name writing variability, we proposed the k-mer/n-gram boolean feature vector sorting algorithm -KOFER. We identified the leaders of the field - China, USA -, characterized the interactions and described the country level features of co-authorship. We observed that the USA were leading in the publication activity until China took the lead 4 years ago. However, the USA are the main co-authorship driver in this field.