this is the option 2 seminar where you listen to class and c…

Option 2: Seminar on Computational Modeling in Biology and Medicine


Computational modeling has emerged as a powerful tool for studying complex biological and medical systems. This seminar aims to explore various aspects of computational modeling in biology and medicine, including its applications, methodologies, and challenges. Through this discussion, you will gain the necessary knowledge to understand the principles of computational modeling and critically analyze its use in solving biological and medical problems.

Seminar Outline

1. Introduction to Computational Modeling

1.1 Definition and Scope of Computational Modeling
1.2 Significance and Applications in Biology and Medicine
1.3 Types of Mathematical Models Used in Computational Modeling

2. Mathematical and Statistical Foundations

2.1 Differential Equations in Biological Systems
2.2 Statistical Modeling and Parameter Estimation
2.3 Sensitivity Analysis and Uncertainty Quantification

3. Biological and Medical Modeling Approaches

3.1 Deterministic Modeling
3.1.1 Ordinary Differential Equations (ODEs)
3.1.2 Partial Differential Equations (PDEs)
3.2 Stochastic Modeling
3.2.1 Gillespie Algorithm
3.2.2 Agent-based Modeling
3.3 Network Modeling
3.3.1 Boolean Networks
3.3.2 Dynamic Bayesian Networks

4. Model Development and Validation

4.1 Model Building Strategies
4.2 Data-Driven Modeling
4.3 Model Calibration and Validation
4.4 Model Selection and Comparison

5. Challenges and Limitations

5.1 Parameter Uncertainty and Identifiability
5.2 Model Complexity and Computational Cost
5.3 Integration of Multi-scale and Multi-level Models
5.4 Ethical and Social Implications

Seminar Questions

1. Define computational modeling and explain its importance in biology and medicine.

2. Discuss the different types of mathematical models used in computational modeling.

3. Compare and contrast deterministic and stochastic modeling approaches in biology and medicine.

4. Explain the concept of network modeling and its applications in biological systems.

5. Describe the process of model development, validation, and selection.

6. Analyze the challenges and limitations of computational modeling in biology and medicine.

Seminar Resources

1. Gerlee, P. (2013). The Modeler’s Toolbox: Computational Tools for Biological Systems. Science, 342(6154), 287-288.

2. Stelling, J. (2004). Mathematical Models in Biology. Nature, 432(7015), 212-215.

3. Ashyraliyev, M., Fomekong-Nanfack, Y., Kaandorp, J., & Blom, J. (2009). Systems Biology: Parameter Estimation for Biochemical Models. FEBS Journal, 276(4), 886-902.

4. Yamada, T., Bork, P., & Lercher, M. J. (2015). Biological Networks in Health and Disease. Genome Biology, 17(1), 1-14.

Seminar Instructions

1. Prior to the seminar, read the assigned resources to familiarize yourself with the topic.

2. Attend the seminar and actively participate in the discussions.

3. Answer the seminar questions in a well-structured and analytical manner, providing evidence from the seminar resources.

4. Submit your completed assignment within the designated timeframe.


Computational modeling is an indispensable tool in modern biology and medicine, enabling researchers to gain insights into complex biological systems. This seminar will equip you with the fundamental knowledge and critical thinking skills necessary to understand and evaluate the applications, methodologies, and challenges of computational modeling. By exploring various topics, such as mathematical and statistical foundations, model development and validation, and the limitations of computational modeling, you will develop a holistic understanding of the field. Through active participation and thoughtful analysis, you will strengthen your ability to utilize computational modeling techniques to address significant questions in biology and medicine.