Key Strategic Goals and Scientific Aims
The ELIXIR CZ Strategy and Programme 2026–2030 sets out an ambitious vision to strengthen the Czech Republic’s position as a leading contributor to the European life-science data ecosystem. Over the next five years, ELIXIR CZ will advance the scientific and technological foundations required for modern data-driven biology, integrating excellence in domain-specific bioinformatics with robust cross-cutting capacities in data management, interoperability, AI readiness, and training. The overarching goal is to ensure that Czech researchers, clinicians, and innovators have access to world-class services, interoperable data, and analytical workflows that meet the highest standards of FAIR and open science.
In this strategic period, ELIXIR CZ will deepen its scientific strengths across four core domains. Structural Bioinformatics will push forward the frontier of AI-driven prediction, large-scale visualization, structural data curation, and rational protein engineering. Chemical Biology will enhance national and European capacities for interoperable linked-data resources, automated ligand-quality assurance, and computational chemistry workflows strengthened by emerging AI methods. Genomics will consolidate and expand its rich ecosystem of databases and tools, introducing AI-enabled querying and multi-omics integration while ensuring that biodiversity, functional genomics, and repeat annotation resources are prepared for large-scale analytics. Human Data will take a decisive step forward with the establishment of the Czech Omics Node (OmiCZ) and Czech FEGA node, creating a national foundation for secure, federated, and clinically aligned genomic data analysis.
These domain areas will be empowered by strong cross-field pillars. ELIXIR CZ will maintain and expand its leadership in Data Management, FAIRification, AAI, and semantic interoperability, driving the transition towards automated, machine-actionable and AI-ready stewardship solutions. The AI/ML and Emerging Methods programme will ensure that modern computational approaches are accessible, explainable, and deployable—including in secure TRE environments for sensitive data. A comprehensive Tools and Training strategy will create a unified and scalable education ecosystem, ensuring that every tool and service is supported by high-quality training while strengthening national capacity across academia, healthcare, and industry. To fulfill these overarching strategies, we will adopt ethical and legal standards reflecting the development and implementation of AI/ML in human data analysis.
Together, these goals define a coherent scientific and strategic mission: to deliver interoperable, AI-ready, and secure data infrastructures that enable Czech science to thrive within the European research landscape, while contributing actively to the development of future European standards, platforms, and federated data systems.
Strengthening Scientific Focus Areas
Structural Bioinformatics: advancing prediction methods, visualization of large structural datasets, AI-driven analysis, curated reference data, and new tools for protein stability, solubility, and engineering.
Chemical Biology: enhancing linked-data infrastructures, interoperability, AI-supported molecular property prediction, and automated ligand curation for high-quality modelling from literature and experimental data.
Genomics: expanding domain databases, improving FAIRification, enabling AI/ML-supported querying, integrating multi-omics and image data, and enhancing repeat annotation and biodiversity platforms.
Human Data: establishing the Czech Omics Node (OmiCZ), building the Czech FEGA node, supporting TRE-based federated analytics, and coordinating national AI activities in multimodal health data.
Cross-field Capacities Supporting All Domains
Data Management & FAIRification: strengthening ELIXIR CZ leadership in Data management via Data Stewardship Wizard, AAI, semantic interoperability, and machine-actionable DMPs; extending stewardship to software, workflows, and AI models.
AI/ML & Emerging Methods: establishing shared resources, training, and guidance for AI adoption across all domains; supporting secure deployment of AI in TREs; leveraging national AI Factory and GPU-enabled infrastructure.
Tools & Training: implementing a unified training platform, integrating online/offline/hybrid modalities, ensuring training for every approved tool or service, and broadening community engagement with workshops and thematic schools.
