Nassim Mahtal

Deep learning extracts MoA-specific signatures from high-throughput images of chemically and genetically perturbed Corynebacteria

This paper develops a deep learning model to identify drug modes of action from high-throughput images of chemically and genetically perturbed Corynebacteria.

Deep learning recognises antibiotic modes of action from brightfield images

This paper uses deep learning to identify antibiotic modes of action from brightfield images without fluorescent labeling, achieving high accuracy in detecting drug exposure and novel mechanisms.

Characterization of emerging Oropouche virus tropism and pathogenicity.

This study investigates Oropouche virus infection in human cell types and its ability to cross the blood-brain barrier, finding broad tropism and neuronal vulnerability.

Bacterial targeting of host paraspeckles uncovers a new SFPQ-based regulation

This study identifies L. pneumophila's LpDot1 protein as a bacterial effector that modifies SFPQ, disrupting paraspeckle organization and host splicing, leading to alternative splice variants of infection-related genes.

Intrinsic differences in hamster and mouse macrophage biology correlate with susceptibility to L. donovani infection

This study compares macrophage biology between hamsters and mice to identify factors contributing to differential susceptibility to L. donovani infection.