Data mining of multi omics data in the context of skeletal tissue engineering
High-throughput sequencing methods such as bulk RNAseq and single cell RNAseq are by now routinely used to acquire vast collection of data for the study of biological systems. The value of these data sets lies in the knowledge that we can distil from it. However, by merely relying on human observation it is not possible to understand, extract conclusions and postulate additional hypotheses using these data. Data mining is a key aspect for both the analysis and understanding of these data. The aim of this project is to develop computational methods and data mining strategies which will provide critical biological insights into the mechanism driving endochondral ossification and will allow the exploration-to-hypothesis-development process leading to further experimental investigations.
lillian.gklava [at] kuleuven.be