All human cells contain the same DNA, yet they look and function differently because they express different genes. This difference is driven by gene regulation, where genes interact in complex networks. Thanks to new technologies and methods, we can study these networks more closely. In this work, we introduce a framework to assess the accuracy of these methods in inferring gene regulatory networks.
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In this project, we investigated a type of RNA molecule known as riboswitches, which play an important role in controlling gene expression in bacterial cells. By using a mix of experiments, large-scale computer simulations and machine learning, we studied how the guanidine-II riboswitch changes shape when binding to specially designed molecules, offering deeper insights into how these genetic switches work.
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