Computational Systems Biology of Cancer
Master in Life Science, ENS
UNBIO1-085/UNBIO1-085 | Computational Systems Biology of Cancer (Curie/Mines/ENS)
Year and Semester : M2+(PhD and Postdocs) | S1
Where : Institut Curie, Paris (first week) - Biology Department, ENS (2nd week and 3rd weeks)
Duration : 1 week + 2 weeks of computational projects (optional, selective)
First and last day of class : September 22th-26th, 2025 (+ two weeks for projects, September 29th-October 10)
Hours : 09:00-13:00 | 14:00-18:00 (susceptible to change)
Maximum class size : 12 IMaLiS students
—2025-2026 programme and applications—
Coordination
Emmanuel Barillot, Institut Curie
Laurence Calzone, Institut Curie
Loredana Martignetti, Institut Curie
Denis Thieffry, École normale supérieure.
Credits
3 ECTS for the first week (E28 - UNBIO1-085)
6 ECTS for the project (E28b - UNBIO1-085)
Keywords
Cancer | Systems biology | Computational biology | Genomics | Proteomics | Tissue imaging | Machine learning
Course prerequisites
M1 level knowledge of genetics, genomics, and cellular and molecular biology for the course.
Bases of python or R programming for the computational project.
Course objectives and description
Aims 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 multimodal data integration and predictive modelling 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 emphasise the role of machine learning methods for understanding the heterogeneity of tumours and applications in personalised treatment schemes development.
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.
IMaLiS M2 students (exclusively) can further apply for a two week-long computational project (granting 6 ECTS, resp. D. Thieffry), based on the content of the article presented during the first week.
Assessment
• The evaluation of the first week 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 on the afternoons of Thursday and Friday during the course 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 and discussion at the end of the last week.
Course material
The schedule and all slides will be made available on Institut Curie’s training website.
Suggested readings in relation with the module content
Barillot E, Calzone L, Hupe P, Vert J-P, Zinovyev A (2013). Computational Systems Biology of Cancer. CRC Press.