Computational Systems Biology of Cancer

Systems biology approaches help to analyse molecular mechanisms in silico The diversity across tumors from different patients and even across cancer cells from the same patient makes the picture very complex, making the fundamental aim to find a common mechanism for therapeutic targeting of cancer becomes unpractical. Therefore, the idea of ‘personalized’ or ‘precision’ medicine has been suggested, aiming to find tailored treatment regimen for each patient according to the individual genetic background and tumor molecular profile. This attempt, although ambitious, is achievable thanks to sufficient molecular characterization of cancers accumulated using high-throughput technologies. However, despite availability of cancer high-throughput (omics) data, they are not fully exploited to provide the clue on deregulated mechanisms that would guide better patients stratification and to specific treatment in cancer.

We invited leading speakers from different fields in cancer systems biology, especially from the field of system biology of single cell data in cancer. The invited speakers will expose various approaches for single cell data analysis and interpretation using cell type-specific pathways resources; tools to study molecular mechanisms of cancer using signalling networks together with omics data from single cells and to associating it to clinical data. In addition, drug sensitivity prediction algorithms, biomarkers and cancer drivers identification; patient stratification approaches; application of mathematical modelling, machine learning and image analysis in cancer approaches with focus on single cell data will be demonstrated.