Mark Bates

VLab4Mic predicts structural resolvability in super-resolution microscopy by simulating imaging configurations and comparing results to experimental data.

This paper introduces COMET, a drift correction method for SMLM that improves resolution and temporal precision, and demonstrates its effectiveness across multiple SMLM techniques.

This paper identifies fluorophore blinking as a source of errors in MINFLUX imaging and demonstrates strategies to suppress these errors, enabling near-infrared MINFLUX with nanometer precision.

This paper introduces SQUASSH, a convolutional neural network that fits structural models to fluorescence microscopy data to quantify variability across biological scales.

This paper introduces a novel laser system for SRS microscopy that achieves 10x faster imaging and color-tuning compared to standard systems.

The paper introduces bacteriophage T4 as a 3D bio-ruler for super-resolution imaging, demonstrating its structure and potential as a benchmark.

This paper introduces a 3D particle averaging method for localization microscopy that improves signal-to-noise ratio and resolution without requiring a structural template.