Nowadays, transcriptomic sequencing data help in the clarification of various diseases. In the laboratory, therefore, large amounts of this type of data are compiled to contribute to the understanding of the biological activities and phenotypes of the diseases. The analysis of the disease-relevant data is highly complex and iterative, since not only known mechanisms and objectives are sought after, but at the same time also new, previously unknown mechanisms. Researchers evaluate again and again lengthy statistical diagrams and Excel tables in order to gain important knowledge. For this, they require not only basic biological knowledge about the diseases, but also proficiency in bioinformatics.

The working group around the bioinformatician Dr. David DeLuca at Hannover Medical School (MHH) has, among other things, set itself the task to support researchers in this painstaking work. As a doctoral student in Dr. DeLuca‘s Team, Bin Liu developed a new interactive web app, which is able to link the expressions of each gene with its biological functions and mechanisms. All necessary tables and diagrams are on display to the scientists in the app in an understandable and easily interpretable way in accordance with the search criteria and are continually automatically updated. Researchers can manage, update and analyse the structurally complicated sequencing data with a minimum use of informatics, whereby they can better concentrate on the interpretation. 

The web app also allows the exchange of data and ideas amongst team members, who are initially working independently on their own subjects and can later share the updated results barrier-free with each other. In addition, Bin Liu’s group works together with  biologists and thus tries to add further useful components directly to the app from practical experience. For example, training on machine learning models is carried out using public data, in order to support a deeper interpretation of sequencing data.  After careful validation and the peer review publication process, these models can also become an important component. 

Currently, there are users within Hannover Medical School (MHH) who actively use the web app for their dissertation or research. In future, the group would like to work together with them and potential users and further improve, develop and promote the web app. They thus hope to continually contribute towards improving their understanding of the transcriptomic data analysis of pulmonary diseases and other areas of biomedical research.
 

Text: BREATH/BL

Photo: DZL