Systems Biology

Question 1

Why use modeling?

Answer 1

when cant answer questions via experimentation or there are too many variables

Question 2

What are features of organizationally complex systems? (4)

Answer 2

1. large number of components
2. large number of processes
3. processes are frequently non-linear
4. small changes in parameters yield completely different phenotypes (important to remember)

Question 3

how many items can the human brain manage at once?

Answer 3

7 +/- 2

Question 4

explain linear vs non-linear situations

Answer 4

linear: no matter what your input, the scaling will always be the same for the output (ex: investment and return)

non-linear: the response of the system is variable, so at different time points there will be different behaviors of the outcome (ex: amount of fertilizer [pretty/dead plants], amount of time in sun[tan/burned]

Question 5

what are examples of non-linear responses

Answer 5

ringing, dampening

Question 6

reduction vs reconstruction: example of each and state which one is tougher to do

Answer 6

reduction: break down system into more detail (population-> individual-> organ, tissue)

Reconstruction: organ/tissue -> individual -> population

reconstruction is harder to do

Question 7

What are the components of modeling:

Answer 7

1. start with LOCAL DATA (information/data/experiments you already have and how the parts work together - most modeling designs are here) and GLOBAL DATA (knowledge of the processes and data you can plug in - from the internet and literature - want to incorporate this into model)
2. Think about what the MODEL STRUCTURE will look like
3. Run DIAGNOSTIC tests to validate the model you created
4. Once model is functioning, understand system via EXTRAPOLATION, MANIPULATION, OPTIMIZATION

Question 8

equilibrium vs homeostasis

Answer 8

equilibrium = no net change in system influences

homeostasis = ability of system to adjust internal environment to maintain stable equilibrium (internal conditions in steady state)

Question 9

sensitivities

Answer 9

slightly changed structure to system

Question 10

gains

Answer 10

inputs to system

Question 11

things that can impact stability (and examples)

Answer 11

1. small perturbation (normal fluctuations)
2. large perturbations (change in environment/large changes in concentration)
3. slightly changed structure (mutation/disease)

Question 12

what is the modeling process

Answer 12

1. idea
2. draft model
3. analyze
4. diagnose
5. bring in data
6. do a reality check
7. refine model
8. bring in more data
9. keep gaining insight into model

Question 13

Reasons to model:

Answer 13

1. check whether pieces of systems, when put together, interact as expected
2. explain how systems work
3. make predictions (eg treatment of a disease)
4. discover design and operating principles
5. develop system simulators