L1: Dynamic models of cellular
metabolism
DATE Jan 29, 2021
DONE
LECTURER Werner Koopman
LEVEL
Revise 1
Revise 2
Revision dates
Revision documents
SLIDES Lecture1_Koopman_Dynamic_Models.pdf
WEEK WEEK 1
Word count 1947
Household regulations
Werner Koopman (course coordinator)
Organisational questions: Mrs. L. Brocatus
Exam: one question for each lecturer (lecture/paper)
a lecturer might ask you to read a paper
Lecture
L1 Dynamic models of cellular metabolism 1
, Systems biology: studying the components of the system which will help to
understand the biology
the interactions between the components of a biological system
how these interactions give rise to the function and behaviour of the
system
In cellular metabolism is mostly energy metabolism done by mitochondria.
What is a model?
Biological models: are used to study physiological and pathological
phenomena (in health and disease).
Computer model: are representations of physiological and pathological
phenomena that are used for predicting the function and behaviour of a
biological system
What types of models exist?
Types of models in biology
Black box vs. grey box vs. white box
Black: no idea about what's going on inside the model
White: which perfectly describes everything in your system
Grey: a model in which part of the system/internal workings is done
These are most models in practise
Linear vs. non-linear
Linear: this input, will give this output (there is an analytical solution)
Non-linear: mostly, you need mathematical analysation
Static (steady-state) vs. dynamic
Deterministic vs. probabilistic (stochastic)
Deterministic: initial conditions determine how the model behaves
Stochastic: statistical processes play a role
L1 Dynamic models of cellular metabolism 2
, Modeling models: a lot of models which differ a lot in complexity
Ordinary differential equations ODEs → today's lecture)
How to choose a modeling method?
With unlimited time and computation resources - choose the modelling
method of the lowest level (quantum mechanics)
It may account for the largest amount of data
It's solutions may converge to higher level solutions if the extra detail is
not needed
Consider Occam's Razor - the simplest explanation in the best
Choose the highest level-of-detail method that can satisfactorily depict
the given phenomenon
Knowledge is a limiting factor
if you don't know every molecule present in a cell, then any stimulation
will obviously be lacking in precision.
If you don't know how molecules behave on the level you are modelling,
then it will be much more inaccurate
Mathematical modelling requires computing power. The more complex
biologically, the more computationally intensive (teraflops).
The systems biology strategy
Mostly the mitochondria are studied
You generate a mouse with a mitochondrial disease and compare this to a
wild type mouse
The idea is that a model is created for both the wild-type and the diseased
mouse. The two models are compared were differences are found, its
learned were it's possible to plan an intervention (treatment).
Basic principles of dynamic modelling
L1 Dynamic models of cellular metabolism 3
, Definition: a dynamic model focuses on how system components influence
rates of change of each component concentration in the model
Result: description of time-varying behaviour of the system
Simulate how the system behaves over time
Governing principle: the law of mass action: the rate of a reaction is
proportional to the product of the concentration of the reactants
Higher concentrations often lead to faster reactions
Key assumptions:
A well mixed environment (no spatial/diffusion effects)
The number of molecules is large (i.e. a continuum of concentrations)
A simple example from reaction kinetics
Reaction 1 AB → C (k1)
Reaction 2 AC → D (k2)
Reaction 3 DB → E (k3)
→ each reaction has its own reaction constant (k)
k1 * A * B = velocity reaction 1 V1 → this can be done for every reaction.
For ODE's you need to consider the generation and the consumption of A
(rate of change).
ODE's are coupled and non-linear
You need a computer to solve the equations
Computer needs: initial conditions (concentrations at the
beginning of the reaction, t=tzero) and the constants
It wil calculate the concentrations over time.
Two examples from our research
Modelling of cellular glucose uptake and consumption in
mouse C2C12 myoblasts
Very simple (minimal model)
L1 Dynamic models of cellular metabolism 4
metabolism
DATE Jan 29, 2021
DONE
LECTURER Werner Koopman
LEVEL
Revise 1
Revise 2
Revision dates
Revision documents
SLIDES Lecture1_Koopman_Dynamic_Models.pdf
WEEK WEEK 1
Word count 1947
Household regulations
Werner Koopman (course coordinator)
Organisational questions: Mrs. L. Brocatus
Exam: one question for each lecturer (lecture/paper)
a lecturer might ask you to read a paper
Lecture
L1 Dynamic models of cellular metabolism 1
, Systems biology: studying the components of the system which will help to
understand the biology
the interactions between the components of a biological system
how these interactions give rise to the function and behaviour of the
system
In cellular metabolism is mostly energy metabolism done by mitochondria.
What is a model?
Biological models: are used to study physiological and pathological
phenomena (in health and disease).
Computer model: are representations of physiological and pathological
phenomena that are used for predicting the function and behaviour of a
biological system
What types of models exist?
Types of models in biology
Black box vs. grey box vs. white box
Black: no idea about what's going on inside the model
White: which perfectly describes everything in your system
Grey: a model in which part of the system/internal workings is done
These are most models in practise
Linear vs. non-linear
Linear: this input, will give this output (there is an analytical solution)
Non-linear: mostly, you need mathematical analysation
Static (steady-state) vs. dynamic
Deterministic vs. probabilistic (stochastic)
Deterministic: initial conditions determine how the model behaves
Stochastic: statistical processes play a role
L1 Dynamic models of cellular metabolism 2
, Modeling models: a lot of models which differ a lot in complexity
Ordinary differential equations ODEs → today's lecture)
How to choose a modeling method?
With unlimited time and computation resources - choose the modelling
method of the lowest level (quantum mechanics)
It may account for the largest amount of data
It's solutions may converge to higher level solutions if the extra detail is
not needed
Consider Occam's Razor - the simplest explanation in the best
Choose the highest level-of-detail method that can satisfactorily depict
the given phenomenon
Knowledge is a limiting factor
if you don't know every molecule present in a cell, then any stimulation
will obviously be lacking in precision.
If you don't know how molecules behave on the level you are modelling,
then it will be much more inaccurate
Mathematical modelling requires computing power. The more complex
biologically, the more computationally intensive (teraflops).
The systems biology strategy
Mostly the mitochondria are studied
You generate a mouse with a mitochondrial disease and compare this to a
wild type mouse
The idea is that a model is created for both the wild-type and the diseased
mouse. The two models are compared were differences are found, its
learned were it's possible to plan an intervention (treatment).
Basic principles of dynamic modelling
L1 Dynamic models of cellular metabolism 3
, Definition: a dynamic model focuses on how system components influence
rates of change of each component concentration in the model
Result: description of time-varying behaviour of the system
Simulate how the system behaves over time
Governing principle: the law of mass action: the rate of a reaction is
proportional to the product of the concentration of the reactants
Higher concentrations often lead to faster reactions
Key assumptions:
A well mixed environment (no spatial/diffusion effects)
The number of molecules is large (i.e. a continuum of concentrations)
A simple example from reaction kinetics
Reaction 1 AB → C (k1)
Reaction 2 AC → D (k2)
Reaction 3 DB → E (k3)
→ each reaction has its own reaction constant (k)
k1 * A * B = velocity reaction 1 V1 → this can be done for every reaction.
For ODE's you need to consider the generation and the consumption of A
(rate of change).
ODE's are coupled and non-linear
You need a computer to solve the equations
Computer needs: initial conditions (concentrations at the
beginning of the reaction, t=tzero) and the constants
It wil calculate the concentrations over time.
Two examples from our research
Modelling of cellular glucose uptake and consumption in
mouse C2C12 myoblasts
Very simple (minimal model)
L1 Dynamic models of cellular metabolism 4
