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Computational Modelling

Machine learning and computational modelling have emerged as powerful tools in both preclinical and clinical research. In this context, hybrid pipelines integrating data clustering, mechanistic modelling, machine learning, and image processing algorithms are being developed to enhance analytical capabilities.

These advancements not only improve automated analysis and decision-making but also provide a stronger mechanistic foundation for understanding complex biological behaviours and making reliable predictions across preclinical and clinical applications.

Neural tube development

Precision skin tumors diagnostics

T-cell commitment

Neurodegenerative diseases modelling

Detection of tumor genes

Transplantable neural cells

Reprogramming to pluripotency