Posts

Here, I will discuss the mapping between the parameters of simplified linear pathway models and the fully enumerated system and the data produced thereof. I will show how the parameters can be estimated analytically through measurements (or prior knowledge) of the mean and the variance of the time at which an output signal is observed. This is then compared to the slower, but more resilient, method of using numerical optimisation. Along the way, we will also gain insight into the reverse problem; given a model with fitted parameters, what can we say about the biological pathway that the model is representing? [Read More]

The Julia programming language provides some very powerful tools for modelling in systems biology. Not only is the language itself superb for scientific programming and heavy computations in general, its package ecosystem really makes systems biology easier to work with. Here, I will show the basic tools that I use when I model and simulate chemical reaction networks. The most important package that I use is DifferentialEquations.jl. I would highly recommend anyone who computes differential equations in any form to read through this documentation thoroughly. [Read More]

I find reductionism invaluable when modelling systems biology. My background in physics has hammered in to me that a model should be as large as it needs to be but no larger. I will by no means argue against heavy reductionism, but I recently came to realise that I have been thinking about models in a way which may not be accurate. When approaching a complicated biological issue with a reductionistic view I often ask myself “What basic interaction logic is causing the dynamics we observe experimentally? [Read More]