eTRIKS

eTRIKS integrates knowledge management and data coordination to support translational medicine research by linking clinical, preclinical, and high-dimensional omics datasets to enable biomarker discovery and analysis.

Key Features:

• tranSMART integration: Integration with the tranSMART knowledge management platform for consolidated handling of study and molecular data.
• Supported clinical data types: Handling of observational clinical cohort data for patient-level analyses.
• Preclinical model data: Support for drug response data from cell culture models and mouse xenograft tumor model data.
• High-dimensional omics linking: Linking of high-dimensional molecular omics data to clinical and preclinical datasets to enable cross-modal analysis.
• Sequencing and molecular technologies: Compatibility with whole genome sequencing and proteomics datasets and with patient-derived biological models and computer-based systems biology simulations.
• Automated data processing: Automation of data mapping, linking, and preparation processes for integrated dataset assembly.
• Consortium-scale coordination: Designed to support large international research consortia, including projects under Horizon 2020 and the Innovative Medicines Initiative.

Scientific Applications:

• Biomarker discovery: Enabling identification and exploration of candidate biomarkers by linking molecular omics to clinical and preclinical outcomes.
• Translational medicine data integration: Coordinating heterogeneous datasets to support translational research questions across clinical and experimental models.
• Multi-omics analysis: Supporting integrated analyses that combine whole genome sequencing, proteomics, and other molecular data with phenotype and drug response data.
• Consortium research use case: Applied within the OncoTrack consortium to manage and analyze complex translational research datasets.

Methodology:

Integration with tranSMART and automated data mapping, linking, and preparation to connect high-dimensional omics data to observational clinical, cell culture drug response, and mouse xenograft datasets.