U900 – Bioinformatics, Biostatistics, Epidemiology and Computational Systems. Biology of Cancer

Teams in this computational unit study several aspects of the cancer pathology through observation of the underlying molecular and cellular mechanisms: initiation (etiology, through the modelling of gene and environment interaction), development and tumor progression (inferring and modelling the gene and protein networks involved, analysis of phenotypes through bioimaging), and improvement in therapeutic strategies (diagnosis, prognosis, design and analysis of clinical trials, identification of therapeutic targets, virtual selection of therapeutic molecules).

Research projects are conducted in close collaboration with biologists and clinicians and always involved a mix of experimental and theoretical approaches, in iterative cycles from the wet biology to the mathematical model and back, which ultimately lead to validated and thus predictive models. They take advantage of new high throughput biological technologies at both the molecular and cellular levels (spectrometry, microarrays, high-throughput cellular phenotyping, deep sequencing) and use state-of-the-art and innovative methods of data integration and systems biology, statistical analysis, high dimension statistical learning, study of complexity, network modeling, virtual screening and bioimaging.


Key publications

Year of publication 2021

Pavel Mozgunov, Xavier Paoletti, Thomas Jaki (2021 Jan 7)

A benchmark for dose-finding studies with unknown ordering.

Biostatistics (Oxford, England) : DOI : kxaa054

Year of publication 2020

Racha Chouaib, Adham Safieddine, Xavier Pichon, Arthur Imbert, Oh Sung Kwon, Aubin Samacoits, Abdel-Meneem Traboulsi, Marie-Cécile Robert, Nikolay Tsanov, Emeline Coleno, Ina Poser, Christophe Zimmer, Anthony Hyman, Hervé Le Hir, Kazem Zibara, Marion Peter, Florian Mueller, Thomas Walter, Edouard Bertrand (2020 Aug 14)

A Dual Protein-mRNA Localization Screen Reveals Compartmentalized Translation and Widespread Co-translational RNA Targeting.

Developmental cell : 773-791.e5 : DOI : S1534-5807(20)30584-0
Pavel Mozgunov, Thomas Jaki, Xavier Paoletti (2020 Jun 13)

Using a dose-finding benchmark to quantify the loss incurred by dichotomization in Phase II dose-ranging studies.

Biometrical journal. Biometrische Zeitschrift : 1717-1729 : DOI : 10.1002/bimj.201900332
Alessandra Meddis, Paul Blanche, François C Bidard, Aurélien Latouche (2020 Apr 28)

A covariate-specific time-dependent receiver operating characteristic curve for correlated survival data.

Statistics in medicine : DOI : 10.1002/sim.8550

Year of publication 2019

Alessandra Meddis, Aurélien Latouche, Bingqing Zhou, Stefan Michiels, Jason Fine (2019 Dec 10)

Meta-analysis of clinical trials with competing time-to-event endpoints.

Biometrical journal. Biometrische Zeitschrift : DOI : 10.1002/bimj.201900103
Peter C Austin, Aurélien Latouche, Jason P Fine (2019 Oct 30)

A review of the use of time-varying covariates in the Fine-Gray subdistribution hazard competing risk regression model.

Statistics in medicine : DOI : 10.1002/sim.8399