The “02 in silico” department offers the following high-value computational and data services, designed to transform hypotheses into validated, optimized frameworks using advanced modeling, simulation, and AI tools.
| Service ID | Service Title | Description |
| 02.01 | Experimental Design | Building robust, reproducible, and hypothesis-driven experimental frameworks grounded in sound statistical principles. |
| 02.02 | Mathematical Model Generation | Creating mechanistic, kinetic, or statistical models that represent complex biological, chemical, or physical systems with clarity. |
| 02.03 | Statistical Analysis | Applying rigorous statistical tools for data validation, pattern recognition, and correlation analysis across large datasets. |
| 02.04 | Plotting and Diagramming | Generating clear, publication-ready figures, charts, and schematics to visualize results, concepts, and workflows. |
| 02.05 | Validation Programming | Developing code-based platforms to test experimental models, verify reproducibility, and benchmark theoretical assumptions. |
| 02.06 | Simulation Techniques | Performing numerical simulations for biological processes, material behaviors, or pharmacokinetic/dynamic predictions. |
| 02.07 | Relative Machine Learning Development | Training custom machine learning models for classification, regression, and prediction tasks tailored to biomedical datasets. |
| 02.08 | AI Establishment | Integrating advanced artificial intelligence approaches—including deep learning, computer vision, and natural language processing—into research pipelines for automation, diagnostics, and intelligent data mining. |
