ABSTRACT / Rare genetic diseases are typically caused by a single gene defect. Despite this clear causal relationship between genotype and phenotype, identifying the pathobiological mechanisms at various levels of biological organization remains a practical and conceptual challenge. In the talk, I will present our recently published work on how network methodologies were used to unify and leverage biological data to address those challenges. Specifically, I will discuss how we constructed a multiplex network consisting of over 20 million gene relationships spanning major biological scales between genotype and phenotype. Our comprehensive analysis of various rare diseases reveals distinct phenotypic modules within individual network layers. We found that these modules can be exploited to mechanistically dissect the impact of gene defects and accurately predict rare disease gene candidates. Our results showed that the disease module formalism can be applied to rare diseases and generalized beyond physical interaction networks. Lastly, I will discuss how these findings open up new venues to apply network-based tools for cross-scale data integration.
BIO / Pisanu ("Ize") is a PhD student in Jörg Menche's group at the Max Perutz Labs of the University of Vienna and CeMM Research Center for Molecular Medicine. His research has centred on network-based data integration to overcome the scarcity of information in certain biological domains, particularly rare diseases. Prior to his doctoral studies, Ize completed his undergraduate degree in physics in Bangkok and later his master's degree in computational systems biology in Helsinki and Stockholm.