SeLS is targeting cross-data use, discovery of new biomarkers, and more powerful integrative analyses. SeLS is aiming to build large-scale semantic-enabled biomedical repositories that will enable analyses on the functional aspect of the underlying biological mechanisms and their associations to diseases into a large integrated knowledge that can be linked, queried, visualised and directly incorporated into analytics. Semantic representation, linking, and reasoning over biomedical repositories may reveal the immensely complex associations and biomarkers, such as epistatic effects, correspondences (linkage) between multi-omics datasets, relation between different –omics markers, phenotypes, and environmental factors. Semantic-enabled biomedical repositories and an underlying integration platform will provide the capacity to functionally interpret knowledge bases and consequently apply this knowledge to develop radically new insights into biology and fundamental mechanisms of disease.

Research Areas:

  • Ontology Building & Alignment: Develop and align existing ontological models for the enrichment, sharing and interconnection between proprietary (i.e. in-silos) and external (i.e. public) healthcare and biomedical repositories
  • Data Linking: Identify and establish prospective links among (i) independently hosted biomedical repositories; (ii) local propriety datasets; and (iii) with the LOD cloud (open datasets)
  • Query Federation:  Develop scalable & federated query mechanisms for complex queries over distributed, heterogeneous, and massive healthcare and biomedical repositories
  • Visualisation: Develop intuitive multi-omics browser/interfaces to explore high-throughput datasets, used to infer biomedical networks and navigate these networks at different magnifications
  • Privacy-Preserving Data Access: Develop inherently privacy-preserving technologies that build confidence amongst data subjects and companies in order to efficiently and legitimately share and utilize their information for agreed purposes