The extraction of useful knowledge from voluminous data produced by high-throughput genomics presents a significant challenge to the scientific community. Efficient mining of this data for the needs of biomedical research critically depends on seamless integration of clinical, genomic and experimental information with prior knowledge about genotype-phenotype relationships accumulated in a plethora of publicly available databases. Furthermore, such experimental data should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.

To address these challenges we are developing Lynx -- a scalable computational platform based on cross-cutting requirements from multiple scientific groups for data integration, management and analysis. The goal of Lynx is to provide an end-to-end support for the analytical needs of various translational projects.