Lisa M. Breckels

The paper introduces SANDLE, a method for analyzing subcellular omics data that reduces false positives and analysis time while handling complex experimental designs.

This study maps the spatial proteome of Plasmodium falciparum schizonts, identifying 24 cellular niches and classifying 1646 proteins, while revealing evolutionary patterns in parasite organelles.

The paper identifies novel proteins that relocalize in adipocytes in response to insulin, highlighting their role in insulin signaling.

This paper introduces a semi-supervised Bayesian method to integrate spatial proteomics data with other omic datasets to improve protein subcellular localization inference.

The paper uses global subcellular proteomics to identify subcellular-specific anti-ferroptotic responses in A549 cells exposed to ionizing radiation, highlighting potential mechanisms of radio-resistance.

The paper introduces BANDLE, a Bayesian method to infer differential subcellular localisation from spatial proteomics data, showing improved accuracy and novel biological insights.

This study evaluates the sub-cellular resolution of 29 spatial proteomics experiments using QSep to provide a quantitative assessment of their ability to resolve sub-cellular niches.

The paper introduces LOPIT-DC, a simplified spatial proteomics method, and compares it with hyperLOPIT, highlighting suborganellar resolution and isoform-specific niches in human cells.