Computational Biology and Omics Data Analysis (CoBiODA)
Présentation
The volume of biological data generated by modern experimental technologies is continuously increasing. Efficient storage, access, and analysis of these highly heterogeneous, multi-omics datasets are essential to the success of large-scale biological research projects. Many research teams and technical core facilities at the institute currently lack sufficient bioinformatics resources and expertise to fully analyze the data they generate, whether in genomics, proteomics, cytometry, or imaging.
Currently, these diverse data types are generally analyzed independently, platform by platform, project by project, and team by team, without a coordinated framework for organizing the bioinformatics resources and expertise required to support these activities. This fragmented approach also limits the transversal integration of datasets generated across the institute’s different technical core facilities.
The objective of the Computational Biology & Omics Data Analysis Group is to organize and structure bioinformatics resources to provide efficient and high-quality research support to IPMC teams, while fostering collaboration within a shared computational framework. Such a structure will establish a strong foundation for interactions among bioinformaticians, consolidate expertise across the institute, and facilitate the integrative analysis of heterogeneous datasets generated by different technical core facilities.
Ultimately, IPMC research teams will benefit from high-level bioinformatics support, enabling more comprehensive and innovative analyses, facilitating the production of high-impact publications, and strengthening the overall scientific output of the institute’s researchers and engineers.
