Driving natural
systems: Enzymes
and metabolic
control analysis
Enzymes and
reaction rates
Driving natural systems: Enzymes and
metabolic control analysis
Metabolic control
analysis
Theorems in MCA
MCA and control
theory
Stoichiometry is not always the fu
Elements of Optimal Control: ICDNS
MSci/MSc
Nick Jones
[email protected]
Optimal Control
What we will cover.
Why this is biologically relevant.
Reviews by Todorov and Kappen [1, 2] are short-ish introductions
and the Bechhoefer review [3] also inc
Elements of Stochastic Optimal Control: ICDNS
MSci/MSc
Nick Jones
[email protected]
Aspects of Stochastic Optimal Control
In this lecture we will particularly briskly investigate selected topics
in Stochastic Optimal Control. Our objective will be
Bridging Inference, Control and Driving: ICDNS
MSci/MSc
Nick Jones
[email protected]
The course so far
We looked at how biological systems might perform inference and
connected to samplers.
We looked at instantiations of deterministic control in t
Driving natural
systems: Chemical
energy production
and use
Chemical energy
and metabolism
Driving natural systems: Chemical
energy production and use
ATP usage and
production
Mitochondria and
bioenergetic
control
Modelling systems
of chemical
reactions
A
Stability of feedback-controlled genetic switches
1. A genetic switch with feedback control.
A common motif in genetic control systems is that of two mutually repressing genes (see Fig. 1).
A
B
B
A
Figure 1: (left) Simple genetic switch. (right) Stem cell
Basics of Control: ICDNS
MSci/MSc
Nick Jones
[email protected]
So far
Review of topics covered in inference course.
How chemical systems can be treated as samplers and can
naturally perform probabilistic inference.
Nick Jones
Basics of Control: IC
Inference Control and Driving of Natural Systems
MSci/MSc/MRes
Nick Jones
[email protected]
The elds at play
We will be drawing on ideas from Bayesian Cognitive Science
(psychology and neuroscience), Biological Physics and
non-equilbrium phenomena
Inference Control and Driving of Natural Systems
MSci/MSc
Nick Jones
[email protected]
Mathematics for Reasoning with Genetic Circuits (better
inference through chemistry)
In this lecture we will provide some of the mathematical tools that
are emp
Sampling I: Inference Control and Driving of
Natural Systems
MSci/MSc
Nick Jones
[email protected]
Sampling I
What we have covered so far.
In the next two lectures we will be providing an explanation of
sampling techniques. These will provide the
Sampling and the Brain: Inference Control and
Driving
Nick Jones
[email protected]
So far
What we have covered so far.
Inference with chemicals and point process models for chemistry
(and neurons).
The problem of normalization.
Sampling (Rejection
Sampling II: Inference Control and Driving of
Natural Systems
Nick Jones
[email protected]
Sampling II
What we have covered so far. The problem of un-normalized
distributions.
Objectives for today:
1
Intuition behind two Markov chain Monte Carlo s