Accèder directement au contenu

Computational Systems Biology of Cancer

Master in Life Science, ENS
Bio-M2_E28b | Computational Systems Biology of Cancer (Curie/Mines/ENS)
Year : 2 (M2) & + (PhD and Postdocs)
Semester : 1 (S1)
Duration : 1 week including Saturday (+ 1 week of computational projects)


Organizers Emmanuel Barillot, Inna Kuperstein, Denis Thieffry.
Co-organizers Chloé Azencott, Yves Moreau, Thomas Walter, Andrey Zinovyev.


3 ECTS (+ 3 ECTS of computational projects)

Course prerequisites

M1 level knowledge of genetics, genomics, and cellular and molecular biology for the course.
Bases of shell scripts, python or R programming for the computational project.
Notice for 2020 : the 2020 edition course will be part of the EMBO/FEBS portfolio and advertised on the EMBO website.
Due to the COVID-19 pandemics, the course might be organised (in part) through video-conferencing.

Course objectives and description

The objective of the course is to promote better integration of computational approaches into biological and clinical labs and to clinics. We aim to help participants to improve interpretation and use of multi-scale data that nowadays are accumulated in any biological or medical lab. This year, the course will particularly focus on Artificial Intelligence (AI) and Machine Learning (ML) approaches in cancer research and in clinics. We will review current methods and tools for the analysis and interpretation of big data, along with concrete applications related to cancer. In particular, we will emphasize the role of AI/ML methods for understanding the heterogeneity of tumours and applications in personalised treatment schemes development. Speakers include leading researchers from different fields in cancer systems biology, especially from the field of Artificial Intelligence (AI) and Machine Learning (ML) in cancer research and in clinics.
Themes : Speakers will expose various approaches for omics, imaging, and clinical data analysis, as well as interpretation combining signalling networks together with multi-scale datasets. They will further cover drug sensitivity prediction algorithms, biomarkers and cancer drivers identification, patient stratification approaches, as well as application of mathematical modelling and image analysis in cancer with focus on AI/ML approaches.


Organisation : the course (granting 3 ECTS for IMaLiS students) is organized at Institut Curie (Paris) over a full week, including Saturday morning, which is devote to a career workshop.
The evaluation is based on the oral presentation of an article related to the topics of the course. Article assignment is organised before the start of the course, while the presentations take place in the afternoons during the course week.
IMaLiS M2 students (exclusively) can further apply for a week-long computational project (granting 3 ECTS, resp. D. Thieffry), based on the content of the article presented during the first week.
The evaluation of the projects is based on the production of a computational notebook (in python and/or R) and on an oral presentation at the end of the week.