What: Free participation, accommodation (for non-local delegates) and meals for members of C1net or another NIBB network
When: Monday 15 January 2018 – Friday 19 January 2018
Where: Park Inn, Nottingham, Nottinghamshire, NG5 2BT
by C1net member, PhD student, Francois Seys
On the 15th of January, about twenty postgraduates gathered in Nottingham to attend a metabolic modelling workshop animated by Prof. David Fell and Dr. Mark Poolman from Oxford-Brookes University. The goal of the workshop was ambitious, yet clear from the beginning: to gain practical insights into the capabilities and limitations of metabolic modelling. The teaching was based on the software package Scrumpy, specifically designed by Dr. Poolman to build structural models of metabolisms. Scrumpy is based on Python, which means that there is no user interface: everything has to be typed in the command line of a Linux operating system. This feature is intimidating at first, but allows a versatility and a transparency that make Scrumpy a perfect teaching tool. I personally enjoyed very much this opportunity to refresh my Python programming skills.
The general introduction was short, quickly laying the foundation of logic and programming necessary for the assembly of our very own metabolic model. It became very clear indeed that the pedagogy was to learn by doing, and thus we started coding as early as the second morning of the 5-days workshop.
The practicals were skilfully assisted by Noah Mesfin, Rupert Norman, Nicole Pearcy, Teresa Diaz Calvo. They each based their PhD on the assembly of the genome-scale model of a different microorganism using Scrumpy, and they each presented their work later in the workshop. They illustrated how genome-scale models could be used to predict the effects of knockouts, expose unexpected pathways, and simulate different culture conditions. It would have been pointless just a few days earlier, but, at that point in time, we were already able to follow a research-level presentation on metabolic modelling. Quite an impressive progression!
The last two practicals saw us building a small metabolic model from scratch and observing the effects of different substrates in a basic central carbon metabolism, in aerobic an anaerobic conditions. What was understood on small models during the workshop can now be applied on larger models within our own projects! Of course we have not quite reached the level of proficiency required to build a genome-scale model ourselves, but that was never the intention. We are now able to communicate effectively with the actual modellers in our teams, we have a starting skillset to keep learning to model and code, and we are aware of what metabolic models can and cannot bring to our research.
“I got a hands on understanding of how to use ScrumPy, and the theory to go with it”.
“I learnt the basic concept of metabolic modelling and the use of ScrumPy software to construct and refine my first model”.
“I have made some very useful contact with academic members and found some common ground for collaboration”.
“The workshop was very useful in facilitating my understanding of metabolic modelling and initiated my process of trying it myself. It also highlighted the assumptions and challenges in modelling, and that’s important for interpreting modelling data”.
100% thought the workshop was very/extremely well organised
91% thought the venue was good/very good/excellent, 9% thought it was fair/poor
91% thought the workshop length was just right
91% thought the pace was about right
100% thought the tutors were very/extremely skilled