Paper on Modelling Leukocyte Motility Released!

plos_cbWell it’s been three years of work in the making, and earlier this week it was finally released. PLOS Computational Biology have published our work on modelling leukocyte motility!

There is a growing body of research interested in how things move. Many biological processes depend on things interacting with one another, and interactions happen when they contact; hence, the interest in motility. Anything from immune cells finding bacteria to lions finding zebras. The main contributions of this paper are to highlight that motility, particularly in 3D spaces, is quite a complex thing to characterise. We show how to use multi objective optimisation in characterising this movement and calibrating motility models to real data. Further, by looking at the quality of models’ fit to experimental data, you can use this approach to select which model best describes the real world system.

We found some other interesting things too. The leukocyte populations we were modelling, neutrophils and T cells, both show negative correlations in speed and rate of changing direction. It’s naive and totally unbiological (I am a computer scientist), but I like to think of someone trying to do a U-turn at 100kph. Not really possible. We also found that cells are individuals in the sense that their respective movements differ from one another. Some are faster, some turn more. Perhaps most interesting, when you take the multi-objective approach, therein assessing models against several criteria simultaneously, the much hailed Lévy flight is not the best description of how these cells move.

densityIt’s been a wonderful adventure in 3D simulation. I’ll be thankful never to have to look at quaternions again. And collision detection between cells in 3D space is also quite a difficult computation to perform. The plan from here is to use this technology to simulate (complete with accurate motility of cells) the onset and resolution of diseases. Or perhaps processes involved therein, the whole hog is quite complex.

Thanks to Tatyana Chtanova, Jon Timmis: co-authors, friends and mentors who helped push this over the line. Oh, wondering what that is a picture of? Read the paper to find out…