Even though we have many facilities and resources at our disposal, we cannot answer all questions concerning our project using laboratory experiments. Moreover, it is not feasible to carry out all possible lab experiments related to our project given our time and resources. Luckily, we can solve these challenges using our modelling skills in so-called dry lab work. In a dry lab, research is being done with the help of computational models that simulate what is happening in the real world.

Our dry lab team is working on two big tasks. Firstly, we are making a software tool that will predict which DNA sequence a researcher has to use for his or her particular experiments. This is needed, because simply taking a gene from one organism and putting it into another is not as easy as it may sound. There are many factors that play a part in whether this process is successful, which introduces a lot of variation between experiments done in different organisms. The aim of our software tool is to minimize this variation, making the outcome of our experiments much more predictable.

Secondly, we are building a model that will simulate how our system will function. That way we can predict if everything will work as expected, even before any experiments have been done in the lab! It will also allow us to predict which experimental conditions will not work, so that we can make informed decisions about our lab experiments beforehand. Lastly, once our model is verified, we can use it to predict how our system will function in new environments in the future.