Abstract

Recent innovations in the fields of genomics and transcriptomics have provided new insight into disease biology at a molecular scale. Much of this data is shared in public repositories, enabling large-scale comparative analysis of disease at the molecular level. Such analysis can reveal shared mechanisms between diseases previously considered to be unrelated, improving our understanding of disease biology and pathology. Further, shared molecular pathways between diseases can suggest new opportunities for drug repositioning (the use of known compounds in new indications), significantly reducing drug development time compared to de novo drug design. In this talk I will outline how different feature spaces of disease can be integrated to associate diseases and drugs at multiple molecular levels.