The DrugLogics team works together with the Lehti Lab to optimise the multiscale representation of ovarian cancer cells and tumours by the usage of Boolean models and discretisation of multi-omics data (genomic, CNV, (single-cell) transcriptomics, (phospho)proteomic, interactome and fluxome data). Especially, the crosstalk signalling of tumour cells and stroma, from a patient-specific perspective, is important.
The DrugLogics team collaborates with the Johansen Lab in the construction of logical models representing T-ALL leukemia and Basal Cell Carcinoma cell fate regulatory systems. The aim of the model simulations will be to analyse the effect of cPLA2 inhibitors on the balance between growth and vigour, like programmed cell death, of the cancer cells.
The DrugLogics team collaborates with the Sueldo Lab to develop a Prior Knowledge Network (PKN) representing controlled signalling cascades determining various types of plant cell death. The aim is to convert these PKNs to logical models that can replicate the effect of death-inducing stimuli during plant development and response to biotic and abiotic stress.
CAG IBD – Precision medicine in Inflammatory Bowel Disease
The DrugLogics team collaborates with CAG-IBD in the construction of a logical model representing epithelial involvement in Inflammatory Bowel Disease (IBD). The aim of the model is to enhance our understanding of how cells of epithelial origin contribute to IBD pathophysiology, and how current and future IBD treatments may interact with epithelial cellular processes.