  The increasing availability of biological data is improving our understanding
of diseases and providing new insight into their underlying relationships.
Thanks to the improvements on both text mining techniques and computational
capacity, the combination of biological data with semantic information obtained
from medical publications has proven to be a very promising path. However, the
limitations in the access to these data and their lack of structure pose
challenges to this approach. In this document we propose the use of Wikipedia -
the free online encyclopedia - as a source of accessible textual information
for disease understanding research. To check its validity, we compare its
performance in the determination of relationships between diseases with that of
PubMed, one of the most consulted data sources of medical texts. The obtained
results suggest that the information extracted from Wikipedia is as relevant as
that obtained from PubMed abstracts (i.e. the free access portion of its
articles), although further research is proposed to verify its reliability for
medical studies.
