Introduction to Systems Biology

“A key feature of present-day biological studies is a reliance on computation.”
- Ingalls

Bioinformatics vs. mechanistic modeling

We are not going to explore bioinformatics. We we investigate “intracellular processes as dynamic systems.”

“The use of such models in molecular biology has been, in the past, hampered by the absence of experimental observations of system behaviour; that is no longer the case.”
- Ingalls

Question: How do you estimate paramaters for a system with hundreds of molecular species and thousands of interactions?

…in systems biology

Definition: A model is a simplified, abstract (or concrete) representation of objects and their relationships and/or processes in the real world.

“Quantitative descriptions of molecular interactions typically invoke the laws of physics and chemistry. The resulting models are thus mechanistic - they describe the mechanisms that drive the observed behaviour.”
- Ingalls

Question: What can I do with a dynamic model?

Answer: Simulation and analysis.

“Whereas simulations indicate how a system behaves, model analysis reveals why a system behaves as it does.”
- Ingalls

Definition: In his book Out of Control (Kelly, 1995), Kevin Kelly defines a system as “anything that talks to itself.”

A system also must have a boundary.

Definition: Most would agree that a system qualifies as complex if the overall behaviour of the system cannot be intuitively understood in terms of the individual components or interactions.

Sound familiar? Concept of emergence!

Two essential features of complex systems:

• Nonlinear interactions or processes
• Feedback loops

Definition: Positive feedback is exhibited when system components increase (excite) their own activity.

Result: Unstable divergent behaviour, but when the mechanism is constrained by saturating effects, can lead to 'locked-in' states and memory.

Examples:

• Exponential growth

Definition: Negative feedback is exhibited when system components inhibit their own activity.

Result: Stabilization (generally), but can lead to instability and oscillations if there is a time lag in the feedback.

Examples:

• Thermostat
• Logistic growth