What is your current role at Fraunhofer ITMP?
Currently at Fraunhofer ITMP, I am dealing with creation of FAIR data and pipelines with help of knowledge graphs. Being at a data-producing center, I leverage this opportunity to interlink in-house produced data with external resources. Knowledge graphs, which are graphical visualization of your data, are a powerful tool that help in linking different data resources into a smaller instance. Hence, such knowledge graph tools immensely reduce the time a researcher would take to get the same information by reading multiple publications. Along with providing knowledge graph tools for supporting researchers across various domains from anti-microbial resistance (AMR) to COVID-19 communities, I provide support for various cheminformatics related analysis relevant for a chemical polypharamacology or side effects. Lastly, I actively take part in creation as well as mapping of ontologies for a given use case.
What do you find particularly exciting about your work?
Not being involved in a group where experts come from a variety of domains previously, the freedom to explore and understand new techniques and learning from experts excites me the most. This gives me the ability to try to solve a given problem in different directions by asking questions like how would a chemist use this information or how would a biologist see these results.
What is your biggest challenge?
The biggest challenge in the work I do remains the uncertainty of the downstream impact of the tools I provide: does the tool help impact the drug discovery process at any given point or does the tool help researchers search for novel targets for already approved drugs or drugs failed in a clinical trail for a specific indication. To overcome this, I try my best to get feedback on the work I do and try to understand the problem statement researchers struggle to answer. This way I can suggest fellow researchers the ways in which tools such as knowledge graphs can be leveraged to solve such problems for them.