The nuclear entry of HIV conceptualized in a digital twin
The Digital Twin
A Digital Twin (DT) is a digital representation of a real-world object or system, accurately simulating its dynamic processes and evolution over time. In our project, we aim to create digital models of human cell segments in molecular detail, allowing them to evolve in virtual reality through advanced simulations. These DTs will continuously improve by integrating experimental data and utilizing high-performance computing and machine learning. The goal is to capture the complex self-organization of molecules within cells and predict the layout and function of subcellular structures. This innovative approach will enable detailed exploration, manipulation, and prediction of cellular behavior in unprecedented detail.
The Digital Twins (DTs) will operate by integrating data and observations into a coherent framework that generates predictions to guide new experiments. This iterative process involves three key steps:
- Building a data-driven, integrative molecular model of a cellular segment.
- Simulating the time-evolution of these cellular segments.
- Evaluating DT predictions through new experiments to refine and enhance the model.
This circular exchange ensures increasingly accurate DTs, providing a quantitative and predictive framework to understand complex biological functions.
Demonstration of the iterative DT cycles applied to the question: 'How Does HIV Pass Its Genetic Information Through a Nuclear Pore Complex?
