  Biological databases can be analysed as a complex network which may reveal
some its underlying biological mechanisms. Frequently, such databases are
identified as scale-free networks or as hierarchical networks depending on
connectivity distributions or clustering coefficients. Since these databases do
grow over time, one would expect that their network topology may undergo some
changes. Here, we analysed the historical versions of miRBase, a database of
microRNAs where we performed an alignment of all mature and precursor miRNAs
and calculated a pairwise similarity index. We found that the clustering
coefficient shows important changes during the growth of this database. For two
consecutive versions of the year 2009 we found a strong modification of the
network topology which we were able to associate to a technological change in
miRNA discovery. To evaluate if these changes could have happened by chance, we
performed a set of simulations of the database growth by sampling the final
version of miRBase and creating several alternative histories of miRBase. None
of the simulations were close to the actual historical evolution of this
database, which we understand as a clear indication of a very strong
construction bias.
