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UID:dc562d84-b8f6-486e-b32a-ef342bdc01fe@oncoplanning
DTSTAMP:20260524T172714Z
DTSTART;VALUE=DATE:20260921
DTEND;VALUE=DATE:20260925
SUMMARY:9th Edition Computational Systems Biology of Cancer : Generative artificial intelligence and network modelling for cancer diagnosis and treatment
DESCRIPTION:The diversity across tumours from different patients and even across cancer cells from the same patient tremendously complicates the development of treatments. ‘Personalized’ or ‘precision’ medicine aims to overcome this problem by finding a tailored treatment regimen for each patient according to the individual genetic background and tumour molecular profile. This ambitious goal requires proper molecular characterization of patient cancer using high-throughput technologies and advanced imaging technologies. Although cancer multi-scale data are becoming available\, these still need to be fully exploited to elucidate the underlying mechanisms and thereby inform patient stratification and treatment. \n\nSince multiple views for the same patients can provide complementary information\, multimodal integrative analysis of omics and clinical data has great potential to elucidate the molecular underpinning of cancer types.  Multimodal integration of disease data holds great promise in uncovering intricate relationships among molecular mechanisms collectively contributing to the disease. \n\nKeynote speaker: Fatima AL-SHAHROUR (CNIO\; Spain)
LOCATION:Amphithéâtre\, "Biologie du Développement" building\, Institut Curie\, Paris\, France
URL:https://training.institut-curie.org/courses/csbc2026
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