IMM events :
The Institut de Microbiologie de la Méditerranée (IMM) organises scientific seminars for researchers every Friday at 11.30am.
These seminars are announced in the Institute’s diary.
The seminar organising committee is made up of :
– Bénédicte BURLAT, researcher at BIP
– Isabelle IMBERT, teacher-researcher at LISM
– Vladimir PELICIC, researcher at the LCB
– Hugo BISIO, researcher at IGS
Seminar information :
– Frequency: Every Friday
– Time: 11.30 a.m.
– Accessibility: These events are not open to the general public. For open events, please consult the public events page.
List of Seminars:
Below is the list of scientific seminars scheduled for the coming month.
If you have any questions or require further information, please do not hesitate to contact the organising committee: seminaires@imm.cnrs.fr
- This event has passed.
Yves BRUN
18 April/11h30 - 14h30
Yves Brun (Department of Microbiology, Infectious Diseases and Immunology, Université de Montréal)
“Exploring New Chemical Space for Antibiotics with Active Learning and Bacterial Phenotypic Profiling”.
Antimicrobial resistance is a major global health threat, yet no antibiotics with a novel mode of action have been approved in the last 20 years. While machine learning (ML) accelerates drug discovery by optimizing molecules in known chemical spaces, it struggles to explore novel spaces where new mechanisms of action might exist. We use Generative flow networks (GFlowNets), a novel ML architecture, to sample chemical space in proportion to a reward function (e.g., predicted antibiotic activity). In this way, compounds with low antibiotic activity, which are discarded as inactive in traditional screening, still provide information that can point in the direction of new antibiotic activity peaks. This approach uncovers pathways to molecules with novel activity. To enhance training, we employ bacterial cell painting, which uses fluorescent dyes to generate detailed phenotypic profiles of compound effects at high throughput. By linking these microscopy profiles to known antibiotics and whole genome CRISPRi depletion data, ML models can infer mechanisms of action. Using high-throughput microscopy screening and iterative ML loops, we aim to identify and validate new antibiotic candidates in unexplored chemical spaces.