Computational Systems Biology of Cancer - Multimodal data integration
The diversity across tumors from different patients and even across cancer cells from the same patient makes the picture very complex. 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 is achievable thanks to sufficient molecular characterization of cancers accumulated using high-throughput technologies and advanced imaging technologies. However, despite availability of cancer multi-scale 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.
Cancer, Clinical research, Prior knowledge, Omics, Spatial transcriptomics, Imaging data, Radiomics, Clinical data, Text mining, Integration,Interpretation, Mathematical modelling, Predictive models for various multi-omics data types,Treatment response prediction and prognosis, Multi-modal data integration.
Inna KUPERSTEIN - Institut Curie - FR
Emmanuel BARILLOT - Institut Curie - FR
Chloé-Agathe Azencott CBIO - MINES - ParisTech - FR
Thomas WALTER CBIO - MINES - ParisTech - FR
Stéphanie ALLASSONNIERE - Université Paris Descartes - FR
Joaquin DOPAZO – IBIS - ES
Denis THIEFFRY - IBENS - ENS - FR
Laurence CALZONE - Institut Curie - FR
Andrei ZINOVYEV - Institut Curie - FR
Mark IBBERSON - SIB - CH
This course is a FEBS-supported event.
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