Fellow | Gergő Gógl

Gergő Gógl is an Inserm researcher and leader of the “Quantitative Interactomics and Disease-Related Networks” group at the Institut de Biologie Valrose (iBV) in Nice, France. With nearly 20 years of experience studying motif-mediated protein interactions, he has pioneered innovative quantitative interactomic approaches that bridge experimental and computational biology. His career includes key contributions to understanding signaling networks, the development of large-scale affinity measurement approaches and analysis tools (e.g., the ProfAff database), and internationally recognized collaborations with experts in proteomics and bioinformatics. Author of over 38 publications (H-index 17), recipient of multiple competitive grants, including the ATIP-Avenir grant, Gergő Gógl is establishing an emerging research hub in systems biochemistry and network-based disease mechanisms in Nice.

This project aims to decode complex interactomes using AI-based tools that integrate quantitative biochemical data with advanced computational modeling. Building on recent breakthroughs in affinity interactomics —which can measure millions of affinities of macromolecular interactions— the project seeks to overcome current limitations in interpreting large-scale interaction networks. By developing novel AI-driven methods, Gergõ's team will identify recurring short linear motifs, infer hidden network topologies, and predict binding affinities of experimentally so-far uncharted interactions, particularly within intrinsically disordered regions often implicated in cancer. Combining experimental data generation and machine learning, this interdisciplinary effort will reveal how mutations rewire cellular signaling, uncover novel cancer driver mechanisms, and establish a new paradigm for quantitative systems biochemistry at the interface of interactomics and artificial intelligence.