Our ‘molecular landscape building approach‘ is an unique method to integrate omics and functional data for any complex disease. Our approach always starts from unbiased genome-wide data, and offers a new platform for data integration, gene enrichment, protein-protein interactions and the application of bioinformatics-based tools. In addition, our data is evidence-based and manually curated to provide the utmost accuracy and reliabilty of the uncovered underlying pathways, and is integrated with corroborating evidence and findings from extensive systematic literature searches and evaluations.

Our landscapes integrate all available omics data. This enables us to identify pathways and themes that are associated with each disease, and generate novel hypothesis about the biological mechanisms underlying the disease.

Based on the molecular landscape of each disease, we can pinpoint converging pathways and protein hubs that are important for disease etiology, and we can identify drug targets. In order to qualify as valid targets, the identified targets have to meet stringent criteria – for example tissue/substrate specificity, temporal specificity, and (additional) function as a biomarker. These drug targets can then be validated in preclinical studies and subsequently used as new leads for drug development.