UH Biocomputation Group - Rene te Boekhorst

Complexity of Biological Systems: Deterministic vs Stochastic Modelling

2018-06-26T12:17:09+01:00

Rene te Boekhorst's journal club session where he discusses the complexity of biological systems and presents the paper "A model of ion channel kinetics using deterministic chaotic rather than stochastic processes (Liebovitch and Toth, 1991)".

In this talk, Rene will highlight some issues concerning the modelling of biological processes. The conventional approach to capture the complexity of biological systems is to focus on their unpredictability and to explain this in terms probability theory, i.e. as stochastic processes. Time series analysis and Markov Chains are popular tools for stochastic modelling and Rene will cover a few fundamental methodological aspects and assumptions of both formalisms. Rene will pay special attention to some terminological confusion concerning the probability distributions underlying Markov models.

If time permits, Rene will compare the results of a stochastic approach with a deterministic view of complexity, illustrated with a rather “heretic” application of chaos theory to model ion-channel kinetics by Liebovitch and Toth (1991).

Date: 29/06/2018
Time: 16:00
Location: LB252

Probability distributions for time durations

2017-05-25T10:26:28+01:00

I will talk about probability distributions for time durations (not time series). I will cover some basic notions of probability theory, random variables and markov models and how these yield / are related to distributions for durations of events.

Date: 26/05/2017
Time: 16:00
Location: LB252

Principal component analysis

2016-10-20T13:30:55+01:00

Principle Component Analysis (PCA) is used by many but understood by few.

In this talk I hope to explain some of the math behind the tool, to raise awareness for its potential (and pitfalls) and to discuss the relationship between PCA and cluster analysis. In addition I will present some examples of its use in neuro-science, from my own work in robotics and an application in economics.

Date: 21/10/2016
Time: 16:00
Location: LB252

Artificial Life: Insights in Simplexity and Complicity

2015-10-27T19:52:02+00:00

In the nineties mathematician Ian Stewart and biologist Jack Cohen teamed up to write "The Collapse of Chaos" (Penguin, 1994). This insightful and at places very funny book explores the shortcomings of classical reductionist science, especially the so called Grand Unifying Theories (or "Theory of Everything") of physics. One of the claims the authors make is that GUTs do not take context into account and therefore are at a loss to explain how on the one hand simple "rules" can lead to highly complex and unpredictable outcomes (even in fully deterministic systems) and on the other hand complexity can lead to simple, global patterns. They illustrate this with examples from real science (mainly physics and biology) but also with (virtual) dialogues with extra-terrestrials and Ada Lovelace, the Victorian founder of computation.

Many of the points Stewart and Cohen make in the book can be found back in condensed form in the attached paper by Ian Stewart (Mathematical Recreations, 1994), which I think is a highly readable and again very funny account of some of the main issues surrounding the Theory of Anything. He illustrates these with a famous "tool-for-thought", a simulation by Chris Langton called "Langton's Ant". These and other topics concerning complexity and simplicity are important themes of the Artificial Life module taught by me and Neil Davey for undergraduate students at the UH. I will use some of the practicals (NetLogo simulations, including Langton's Ant) of the module and final year projects inspired by them to instigate a discussion about complex systems.

(Attachment)

Date: 30/10/2015
Time: 16:00
Location: LB252