Steve Pressé

This study reveals that Hsp104, an AAA+ ATPase, functions as a bidirectional, processive translocase by switching direction through biased stochastic conformational transitions.

This paper introduces BNP-FRET-Bin to resolve FRET signal degeneracy and population heterogeneity by inferring state numbers and kinetics directly from FRET data, revealing new biologically relevant states.

This study shows that stochastic colonization and host-to-host transmission significantly influence gut bacterial variability in C. elegans using E. coli under different diets.

This study investigates how pore-1 loops of ATPase subunits in the 26S proteasome affect substrate degradation efficiency using biochemical and single-molecule assays with yeast proteasomes.

This paper introduces a GPU-accelerated framework for processing 3D multiplexed RNA-FISH data, quantifies information loss from axial sampling, and improves post-mortem sample quality.

This paper introduces a Bayesian S-FLIM framework that learns spectra and lifetimes photon-by-photon, enabling efficient deconvolution of up to 9 fluorophore species with overlapping spectra.

The paper introduces MAESTRO, a multi-axial force application method, revealing hidden conformational dynamics in Holliday junctions under complex mechanical environments.

QTrack improves particle tracking by directly modeling quantized photon detections, achieving faster and more accurate results than traditional methods.

This paper infers binding and unbinding rates from fluorescence time series while accounting for photobleaching using a two-stage Bayesian approach.

This paper develops a framework for simultaneous particle tracking, phase retrieval, and PSF reconstruction to improve 3D tracking of lytic granules in T cells.

The paper uses Bayesian nonparametric methods to analyze residence times of cholesterol interactions with GPCRs in MD simulations, revealing kinetic rates and molecular events.

REPOP reconstructs bacterial populations from platecounts by accounting for dilution and plating uncertainties, revealing hidden multimodality that standard methods obscure.

This paper introduces B-SIM, an unsupervised Bayesian framework for structured illumination microscopy that improves resolution and contrast by accurately modeling noise, outperforming existing methods in both simulated and experimental data.

This paper introduces SP2T, a method for tracking fast-diffusing particles using 1-bit image data, showing it outperforms traditional methods and enables faster, more accurate tracking.

The paper develops a Bayesian method using Gaussian Processes to map diffusion coefficients continuously across membranes from particle trajectories without data binning.