Integrative Bioinformatics and Systems Medicine research projects usually require the management and integration of heterogeneous (pre-)clinical and experimental big data. Often, such projects involve complex data analyses from bioinformatics, machine learning or mathematical modeling. Furthermore, the FAIR principles suggest rich and harmonized annotation, controlled access, interoperability and sustainability of data and results. Finally, analyzing, exploring, sharing and discussing data and results among the project partners creates iterative cycles, which can be substantially accelerated by a homogenized digital platform with intuitive and interactive interfaces for the aforementioned tasks.

Semares™ is a software technology framework designed for the configuration and development of integrative bioinformatics and systems medicine digital platforms. It supports data management and integration according to FAIR principles through a configurable semantic layer and user-friendly interfaces. The platform includes a workflow subsystem that enables the integration of complex bioinformatics analyses as push-button apps. Preconfigured and customizable interactive visualization plugins allow users to explore data and results and connect to external knowledgebases. Semares™ is easy to set up and maintain, featuring a configurable data privacy layer. It is utilized in various national and international research projects to identify biomarkers from multi-omics data, connect clinical and experimental data, and facilitate end-to-end research use cases.