Network Science in Medicine: A White Paper

Francesco Bullo; Pietro Hiram Guzzi

Recent years have seen a remarkable rise in the number of applications of network science in
the fields of biology and medicine. Networks in biology and medicine aim to represent the
organisation of living systems as a set of interacting elements at different scales, from the
subcellular to the population level. The initial application of network science in medicine
primarily focused on understanding the structure of protein interaction networks and using
these relationships to hypothesize new disease genes or novel therapeutic targets. At the same
time, network science has been widely applied in the context of molecular biology, for example
to model biological processes as gene regulatory networks. Now, with the continual influx
of biomedical big data, which is providing increasingly detailed information about various
aspects of molecular biology and medicine, the scale and scope of the network models used in
biology and medicine have skyrocketed. For example, improvements in medical imaging has
greatly facilitated the study of brain interaction networks.
Moving forward, it is imperative to develop approaches that holistically model the
complexity inherent in biological systems. Network science, in particular, has the potential to
answer critical questions in medicine that cannot be addressed through standard approaches.
By capitalizing on tools designed to quantify the fundamental properties of large-scale complex
systems, network science offers a complementary view to that of systems biology, which
tends to focus on basic mechanisms and small to medium-scale biological models. We believe
there has never been a better opportunity to employ network science to make sense of large,
complex biological systems and tackle some of medicine’s most challenging open questions. In this white paper, we review several key areas where network science has the best opportunity to contribute to medical applications and posit several critical future directions for the field.