Carlas Smith

This study quantifies spatio-temporal image degradation from motion blur in fluorescence microscopy using SSNR and simulations, showing resolution loss up to 40% for 90-degree motion direction changes.

This paper benchmarks predictive modeling and control techniques with optogenetics to steer nucleocytoplasmic transport in mammalian cells, showing robust performance against cell-to-cell variation.

This paper introduces outcome-driven microscopy, combining optogenetics and smart microscopy to achieve precise control over cellular behavior through predefined outcomes.

This paper develops a deep learning model to automate microtrace recognition in forensic microscopy, reducing manual annotation needs by 65% through combined pretraining strategies.

This paper introduces a model-based method to estimate field-dependent aberrations in single molecule localization microscopy without calibration, improving localization accuracy across large fields of view.

This paper introduces SIMCODE, a method combining modulation patterns and deep learning to enhance single-molecule localization microscopy, achieving better resolution and performance in high-density samples.

CLEAR-IT improves cell phenotyping in tumor microenvironments by using contrastive learning, outperforming existing methods across imaging modalities and requiring fewer labels.

This paper introduces a spline-based method for depth-dependent PSF calibration in localization microscopy, improving PSF accuracy and localization precision.

This paper proposes tiered metadata specifications for light microscopy to improve data quality, reproducibility, and interoperability, inspired by genomic standards like Encode.

The paper localizes specific mRNAs in Drosophila Mushroom Body Output Neurons before and after aversive olfactory learning, showing cell-specific abundance and a transient increase in CaMKII mRNA.

This study identifies Syncrip/hnRNPQ as a regulator of activity-induced Msp300/Nesprin-1 expression and new synapse formation through local translation.

The paper improves single molecule localization precision using patterned illumination in a conventional setup, achieving near twofold better precision than standard methods on DNA-origami structures.

The paper introduces an automated Bayesian pipeline for analyzing single-molecule binding data and benchmarks it using TtAgo binding properties.

This paper applies single-molecule FISH to study post-transcriptional regulation in Drosophila brains by analyzing mRNA distributions and co-visualizing transcripts and proteins.

The paper evaluates the reliability of 3D-SPEED, a method that reconstructs spatial transport distributions in the nuclear pore complex from 2D images.