8th edition - Computational Systems Biology of Cancer
Multimodal data analysis and network modelling to master cancer hallmarks
The course will gather leading speakers from different fields in cancer systems biology, in cancer research and in clinics. The invited speakers will expose various approaches for omics, imaging, clinical data analysis and interpretation, combining signalling networks with multi-scale molecular data, as well as with clinical data.
More specific topics include multimodal genomic data integration and analysis, drug sensitivity prediction algorithms, identification of biomarkers and cancer drivers, patient stratification, and applications of mathematical modelling and image analysis in cancer.
This edition will further include novel sessions devoted to current applications of natural language processing in computational systems biology of cancer, to the integration of epigenomic data, as well as to systemic pharmacology and metabolomics approaches. Finally, a highlight of the meeting will be the celebration of the 25th anniversary of the publication of the landmark article on Cancer Hallmarks by Hanahan & Weinberg (Cell 2000).
Objectives
The goal of the course is to promote computational approaches in biological and clinical laboratories. We aim to help participants understand and utilise multimodal integration approaches to effectively leverage the various types of data accumulating in most biological or medical labs.
The course will review current methods and tools for analysing and interpreting multimodal genomic data, with a focus on natural language processing and network approaches, as well as concrete applications related to cancer.
In particular, the course will present computational methods that allow us to deepen our understanding of tumour heterogeneity, make use of multimodal integration of clinical and omics data, and design personalised treatment regimens.
The invited speakers will expose various approaches for omics, imaging, clinical data analysis and interpretation, combining signalling networks together with multi-scale molecular data, further associating with clinical data.
They will further review current methods and tools for the analysis and interpretation of pangenomic data, with a special focus on recent spatial transcriptomics and proteomics, along with concrete applications related to cancer.
More specific topics include multimodal data integration and analysis, drug sensitivity prediction algorithms, identification of biomarkers and cancer drivers, patient stratification, and applications of mathematical modelling and image analysis in cancer.
Application deadline: 15 June 2025
Keynote speakers
Elsa BERNARD (Gustave Roussy, FR)
Luca PINELLO (MGH/Harvard Medical School/BROAD Institute, US)
Speakers
Annabelle BALLESTA (FR)
Kyra BORGMAN (FR)
Laurence CALZONE (FR)
Michele CASELLE (IT)
Giovanni CIRIELLO (CH)
Leanne DE KONING (FR)
Aurélien DUGOURD (DE)
Asmund FLOBAK (NO)
Laurent GATTO (BE)
Vassily HATZIMANIKATIS (CH)
Frédérique LISACEK (CH)
Marta LOVINO (IT)
Loredana MARTIGNETTI (FR)
Yves MOREAU (BE)
Kristin REICHE (DE)
Nicolas SERVANT (FR)
Angélique STEPHANOU (FR)
Thomas WALTER (FR)
Lodewyk WESSELS (NL)
Andrei ZINOVYEV (FR)
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