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Published on: April 23, 2021
Engineering simulations for cancer systems biology
James Bown1, Paul S Andrews, Yusuf Deeni
1Institute of Arts, Media and Computer Games, University of Abertay Dundee, Dundee, UK. j.bown@abertay.ac.uk
Current Drug Targets
|September 15, 2012
Summary
Computer simulations are powerful scientific instruments. This framework enhances their development for cancer systems biology, improving experimental design and reproducibility.
Area of Science:
- Computational biology
- Systems biology
- Cancer research
Background:
- In silico models accelerate hypothesis generation and experimental design.
- Developing simulations as reproducible scientific instruments requires high standards.
- Challenges include data scarcity and evolving knowledge in cancer research.
Purpose of the Study:
- To present a framework for developing computer simulations as scientific instruments.
- To address challenges in cancer systems biology, focusing on cellular signaling models.
- To enhance the integration of computational models with biological experimentation.
Main Methods:
- Separating scientific and engineering concerns in model development.
- Employing an argumentation approach for documenting assumptions and knowledge gaps.
- Utilizing interactive, dynamic visualization tools for biological community engagement.
- Applying concurrent programming to bridge scale discrepancies in multi-scale modeling.
Main Results:
- A framework supporting the development of simulations as scientific instruments.
- Methods to address data limitations and knowledge gaps in cancer modeling.
- Interactive tools for direct engagement with cellular signaling models.
- A strategy for developing multi-scale models using concurrent programming.
Conclusions:
- The proposed framework facilitates the creation of robust, reproducible computational models.
- Interactive visualization and concurrent programming are key to advancing multi-scale cancer modeling.
- This approach supports the development of biologically plausible models for understanding cancer and therapeutic responses.
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