  Despite the importance of scientific software for research, it is often not
formally recognized and rewarded. This is especially true for foundation
libraries, which are used by the software packages visible to the users, being
``hidden'' themselves. The funders and other organizations need to understand
the complex network of computer programs that the modern research relies upon.
  In this work we used CZ Software Mentions Dataset to map the dependencies of
the software used in biomedical papers and find the packages critical to the
software ecosystems. We propose the centrality metrics for the network of
software dependencies, analyze three ecosystems (PyPi, CRAN, Bioconductor) and
determine the packages with the highest centrality.
