Network Medicine

Biological information can be represented as networks in which nodes represent entities (e.g. proteins) and edges the relationships between them (e.g. physical interactions between proteins). By using a network representation, we can leverage on methods from network science to model biological processes underlying human diseases, and also to model the mode of action of drugs (therapeutic but also toxic effects). For instance, we are interested in the network properties of disease genes and how these properties relate to their tolerance to germ-line genetic variation. This type of information can be useful for methods to prioritize genetic variants identified from large scale sequencing projects. We also apply network biology approaches to understand the biological mechanisms underlying disease comorbidities, and to model the molecular basis of the undesired effects of drugs.

The term network medicine was originally coined by Pawson & Linding to refer to a network-based approach to study human diseases. Under this view a disease arises as a consequence of genetic and environmental perturbations of cellular networks.

Network medicine allows:

  • system-based charachterization of the biological processes underlying a disease
  • the development of network-based drugs and drug repurposing
  • the study of the inter-relations between phenotypically different diseases by shared molecular pathways (e.g. comorbidities)

Current projects in our group involve:

  • Study of the biological basis of disease comorbidities
  • Study of the biological processes underlying drug toxicity and adverse drug reactions
  • Network properties of disease genes and their relation to germ line mutation

Related tools: DisGeNET, ADR-Substantiation

Related publications

Solène Grosdidier, Antoni Ferrer, Rosa Faner, Janet Piñero, Josep Roca, Borja Cosío, Alvar Agustí, Joaquim Gea, Ferran Sanz, Laura I Furlong. Network medicine analysis of COPD multimorbidities. Respiratory Research 2014, 15:111  doi:10.1186/s12931-014-0111-4

Furlong LI. Human diseases through the lens of network biology. Trends in genetics, 2012; 29 (3):150-159. PMID: 23219555 . DOI: 10.1016/j.tig.2012.11.004.

Bauer-Mehren A, van Mullingen EM, Avillach P, Carrascosa MC, Garcia-Serna R, Piñero J, Singh B, Lopes P, Oliveira JL, Diallo G, Mestres J, Ahlberg Helgee E, Boyer S, Sanz F, Kors JA, Furlong LI. Automatic filtering and substantiation of drug safety signals. PLoS Comput Biol. 2012 Apr;8(4):e1002457. Epub 2012 Apr 5. PubMed

Anna Bauer-Mehren, Markus Bundschus, Michael Rautschka, Miguel A. Mayer, Ferran Sanz, Laura I. Furlong. Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases.  PLoS ONE 2011 6(6): e20284. doi:10.1371/journal.pone.0020284. PubMed

Bauer-Mehren A, Rautschka M, Sanz F, Furlong LI. DisGeNET – a Cytoscape plugin to visualize, integrate, search and analyze gene-disease networks. Bioinformatics. 2010 Nov 15;26(22):2924-6. Epub 2010 Sep 21.PubMed