At BREATH, the Hannover site of the German Center for Lung Research, Bin Liu, together with members of the Bioinformatics Platform and experimental biologists, is working on methods to evaluate RNA data which should help to clarify various diseases. In her prizewinning project, Liu searched for a more effective and stable approach for the interpretation of transcriptomic sequencing data. This type of data is widely used to contribute to the understanding of the biological activities in underlying diseases. To do this, it is usual to consolidate many genes into so-called pathways or gene sets that have previously been defined in different ways. In the presented work, the reliability of the current standard procedure was evaluated and compared with an alternative method, in which the genes were grouped together according to their activity in previous transcriptome experiments.

For this project, Liu developed a data set that concentrates on immunological processes and she compared the robustness and performance of the new method with the current standard method. The results showed that the genetic signature approach derived from the data is a valid and helpful tool which can be used as an alternative to the traditional approach. Based on these results, Liu hopes that her method can broaden the basic knowledge in this area of immunological research and thus contribute to a better understanding of (end-stage) pulmonary diseases.

In the future, Liu and her colleagues would like to further optimize these methods and include them in the repertoire of standard methods, to thus contribute to the understanding of the transcriptomic profiles of pulmonary diseases.