Development of individual-specific molecular networks (ITN-PhD Position @ BIO3 KU Leuven))

Describing a system implies describing its behaviour and important control mechanisms that regulate this behaviour. Crucial in this process are interactions, which may occur at different levels or scales, and thus network theory and network visualization are increasingly being used to understand biological mechanisms operating in human systems. However, an individual, especially when in poor health, is likely to deviate from the “norm” in human systems. In this project, we wish to develop omics data integrative gene-based networks to enhance Precision Medicine. Such a network would enable the identification of gene modules that are subject-specific (in network nodes/edges) and comprise multi-layer cellular information. It goes beyond existing work in that genes are considered to be complex multi-omics systems, and that statistical significance is assessed for individual-specific nodes/edges (in contrast to f.i. Menche et al. 2017 and Kuijjer et al. 2018). We aim to achieve our goal by building upon the aforementioned references and our work on gene representations using diffusion kernels and network theory (Fouladi et al. 2018). Personalized gene omics-integrative signatures will primarily be derived by combining genome, transcriptome and epigenome data for complex diseases with an inflammatory component.

The project outcome will lead to an integrative workflow for patient-specific prognostic or predictive biomarker discovery. The opportunity to carry out secondments at Institut Pasteur (France – Prof Benno Schwikowski) and the Golden Helix Foundation (UK – Prof George Patrinos), will further foster assessing the general feasibility of the developed techniques towards clinical application, formulating preliminary guidelines regarding multi-target (rather than single-target) drug strategies, and making recommendations about drug efficacy study designs.

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