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 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
Collier Olivier, Stoven Véronique, Vert Jean-Philippe (2019 Sep 25)

A Single- and Multitask Machine Learning Algorithm for the Prediction of Cancer Driver Genes

Plos Computational Biology
Slim L., Chatelain C., Azencott C.A., Vert J.P. (2019 Jun 1)

kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection

International Conference on Machine LearningInternational Conference on Machine Learning : 5857-5865
PONS-TOSTIVINT Elvire, LATOUCHE Aurélien, VAFLARD Pauline, RICCI Francesco, LOIRAT Delphine, HESCOT Ségolène, SABLIN S Marie-Paule, ROUZIER Roman, KAMAL Maud, MOREL Claire, LECERF Charlotte, SERVOIS Vincent, PAOLETTI Xavier, LE TOURNEAU Christophe (2019 Feb 6)

Comparative Analysis of Durable Responses on Immune Checkpoint Inhibitors Versus Other Systemic Therapies: A Pooled Analysis of Phase III Trials

JCO Precision Oncology : DOI : 10.1200/PO.18.00114
Peter Naylor, Marick Lae, Fabien Reyal, Thomas Walter (2019 Feb 5)

Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map.

IEEE Transactions on Medical Imaging : 448-459 : DOI : 10.1109/TMI.2018.2865709