Modern analytical methods in genomics, transcriptomics, proteomics, and metabolomics generate large and complex datasets. The aim of the MultiOmics Data Science working group is to support in analyzing, integrating, and interpreting these data. By integrating different omics layers, biological processes can be understood more comprehensively, and new insights can be gained for agriculture, food quality and health. In this context, we work closely with the MultiOmics Centre for Food and Health (MOC).

In our laboratory at NOI Techpark, we can perform long-read sequencing in-house using Nanopore technology, enabling us to address questions in genomics and transcriptomics. The subsequent data analysis is carried out on our own workstation; for particularly computation-intensive analyses, we additionally use the computing capacities of the HPC cluster within the framework of the MultiOmics Centre for Food and Health (MOC). In this way, we combine laboratory work, bioinformatics, and data integration into reproducible workflows and practice-oriented results.

Examples from our work:

• Analysis of epigenetic changes in leaves affected by apple proliferation, to better understand how disease symptoms develop.
• Creation of a database of volatile organic compounds (VOCs) to better identify aroma compounds in different foods and plants using gas chromatography–mass spectrometry (GC-MS).