Research activity

Franck Giacomoni (FG) is a research engineer at INRAE and has been contributing to the activities of the Human Nutrition Unit (UNH) since 2018. He has over 15 years of experience in academic metabolomics and computational biology. In his roles as project manager and head of the INGENUM unit (UAR1413), he designs and implements IT infrastructures dedicated to storage, computing, and virtual research environments, with a particular focus on data science approaches applied to metabolomics.

Involved in numerous national and European projects, FG notably coordinated Workflow4Metabolomics (W4M), an international portal dedicated to the reproducible analysis of metabolomic data. He has also led the development of databases such as PhytoHUB and PeakForest, facilitating the annotation and integration of complex omics data. As a member of the executive committee of the national MetaboHUB infrastructure, he coordinates initiatives related to digital infrastructure and the dissemination of FAIR data. As a French representative within ELIXIR, he leads a research program (2024–2028) aimed at enhancing the reproducibility and interoperability of metabolomics workflows.

As part of the VARIAe team, his work focuses on integrating artificial intelligence methods (particularly NLP and LLM) and leveraging linked open data to build innovative knowledge bases for interpreting metabolomic data and developing tools for personalized nutrition.

Publications

Franck Giacomoni, Gildas Le Corguillé, Misharl Monsoor, Marion Landi, Pierre Pericard, et al..Workflow4Metabolomics: A collaborative research infrastructure for computational metabolomics. Bioinformatics, 2015, 31 (9), pp.1493-1495. https://doi.org/10.1093/bioinformatics/btu813

Maxime Delmas, Olivier Filangi, Nils Paulhe, Florence Vinson, Christophe Duperier, William Garrier, Paul-Emeric Saunier, Yoann Pitarch, Fabien Jourdan, Franck Giacomoni, Clément Frainay, FORUM: building a Knowledge Graph from public databases and scientific literature to extract associations between chemicals and diseases, Bioinformatics, Volume 37, Issue 21, November 2021, Pages 3896–3904, https://doi.org/10.1093/bioinformatics/btab627

Paulhe, N., Canlet, C., Damont, A. et al. PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management. Metabolomics 18, 40 (2022). https://doi.org/10.1007/s11306-022-01899-3

Witting, M., Malik, A., Leach, A. et al. Challenges and perspectives for naming lipids in the context of lipidomics. Metabolomics 20, 15 (2024). https://doi.org/10.1007/s11306-023-02075-x

Hajjar, G., Giacomoni, F., Umec, M. et al. Metabolite names and identifiers: how far are we from interoperability?. Metabolomics 22, 28 (2026). https://doi.org/10.1007/s11306-026-02404-w

Other links

• Google Scholar : https://scholar.google.co.uk/citations?user=su_-kmkAAAAJ&hl=en
• ORCID : https://orcid.org/0000-0001-6063-4214
• HAL: https://hal.inrae.fr/search/index/?q=authFullName_t%3A(%22Giacomoni+Franck%22+OR+%22G+Franck%22)+OR+authIdHal_i%3A181685&rows=50&sort=publicationDate_tdate+desc&page=1
• LinkedIn: https://fr.linkedin.com/in/franck-giacomoni-1979a074