Computational Biology & Medical Data Intelligence Group (CBMD Group)

Key Research Questions & Hypotheses

1. How can foundation models accurately predict cellular state transitions under unseen genetic and chemical perturbations?
2. What privacy-preserving cryptographic protocols allow multi-hospital federated training on sensitive clinical genome records?
3. How can topological deep learning capture complex 3D chromatin folding dynamics?

Methodologies & Technical Approaches

1. Building graph transformer architectures tailored for heterogeneous biological networks and spatial transcriptomics.
2. Implementing secure multi-party computation (SMPC) and differential privacy mechanisms for clinical cohort analysis.
3. Benchmarking predictions against experimental validation datasets in collaboration with Warsaw Medical University.

Facilities, Compute & Equipment

• Dedicated secure enclave computing environment meeting strict GDPR health data compliance standards.
• Open data pipelines conforming to ELIXIR European biological data repository guidelines.

Key Scientific Publications & Foundation Works

Selected foundation literature and methodology references utilized by the laboratory team.