Mots-Clés

omics multi-omics computational biology bioinformatics oncology

Description

The generalization of new generation sequencing data (i.e., multi-omics: genomics, transcriptomics, proteomics,) as well as the emergence of new methods (single cell sequencing, spatial transcriptomics) opens new research horizons on cancer pathologies. These data, of very large dimensions and volume, bring new methodological challenges in terms of statistical and mathematical analysis, as well as computational modeling. The development and numerical implementation of novel methods has become a key issue in modern oncology, both in terms of understanding the biology of cancers and for medical oncology. On the first aspect, the analysis and modeling of these data is, for example, fundamental for the study of key phenomena such as intra- and inter-tumor heterogeneity of cancer cells and their microenvironment. On the other hand, the integration of multi-omics data into predictive artificial intelligence models will allow the development of precision medicine based on personalized treatments.

One of the Center for Research on Cancer of Marseille (CRCM)'s current strategic priorities is to strengthen bioinformatics and data science, and specifically the analysis of multi-omics data that are becoming prominent in cancer research. This momentum has materialized through the recent creation (2021) of a joint team with Inria (National institute for applied mathematics and computer science): COMPO (COMPutational pharmacology and clinical Oncology). COMPO is one of the few Inria-Inserm joint teams at the national level, the only Inria team located in Marseille, and the sole team specialized in digital aspects at CRCM. This multidisciplinary team (clinicians, pharmacologists, and mathematicians/data scientists) nevertheless faces a shortage on the digital side, with only one permanent researcher (Inria) and a professor close to retirement. The CRCM therefore wishes to reinforce its computational human resource at an excellent level, with an ideal environment for fruitful joint research with multiple CRCM teams (e.g., predictive oncology, pancreatic cancer, REMAP-4Kids,...). A Chair focusing on this specific profile (multi-omics data modeling) addresses both a strong need of CRCM's research teams and would also bring new and complementary skills to those already existing within COMPO (mechanistic modeling of dynamic data in clinical oncology).

This recruited researcher will aim at developing cutting-edge computational methods to leverage multi- omics and single-cell resolution data into novel and translational discoveries in cancer research. This will be performed in synergistic interaction with the other CRCM teams.