Julia Mahamid

This paper introduces a multiscale correlative imaging workflow for cryogenic specimens, enabling fluorescence-guided site preparation and targeted lamellae lift-out for cryo-ET.

The paper develops spatially-resolved models of the yeast galactose switch to show how intracellular organization affects regulatory dynamics.

This study visualizes human pre-ribosome assembly in nucleoli using cryogenic correlative light and electron tomography, revealing structural states and interactions.

The paper identifies and characterizes a non-canonical bacterial protein translocation-folding complex using cryo-electron tomography, proteomics, and structure prediction in Mycoplasma pneumoniae.

EasyGrid automates cryo-EM sample preparation and quality control, improving vitrification for macromolecules and mammalian cells.

This study shows seipin undergoes conformational changes at the ER-LD interface, enabling lipid droplet growth and regulated lipid storage.

This paper introduces a modular cryogenic light microscope for single-molecule localization microscopy, improving stability and reducing ice contamination in cryo-CLEM.

This paper demonstrates that cryo-FIB lamellae allow higher excitation laser intensities in SR-cryo-CLEM, improving localization precision and imaging speed.

The paper optimizes data quality and completeness in cryo-ET experiments by analyzing processing parameters to improve annotation and structural characterization of macromolecular complexes.

The paper investigates the structural basis of stress-induced cytoplasmic solidification in yeast, finding that acidification drives supramolecular assembly rather than uniform crowding.

CryoSiam is a self-supervised framework for cryo-ET data analysis that learns hierarchical representations and transfers to experimental data for denoising, segmentation, and macromolecular detection.

The paper uses cryo-electron tomography to visualize bacterial translation processes in Mycoplasma pneumoniae, revealing structural coordination between transcription, translation, and membrane attachment.

The paper designs orthogonal fluorophore-binding proteins using deep learning for multiplex imaging, demonstrating high specificity and utility in labeling and monitoring subcellular processes.

This study investigates how cooling temperature, immersion medium, and EM grid material affect devitrification in cryo-SMLM, showing that metallic supports in cold nitrogen tolerate higher laser intensities.

The paper introduces HMFF, a method integrating experimental data into membrane simulations, and applies it to various biological systems to enable multi-scale modeling.

The paper uses cryo-electron tomography to visualize centrosomes in C. elegans embryos, revealing structural features and differences in microtubule organization during the cell cycle.

The paper describes a protocol for subtomogram averaging to generate high-resolution density maps of helical filaments using cryo-electron tomography, applied to mumps virus nucleocapsids and in-cell forms.

ColabSeg is a tool for processing and visualizing membrane segmentations from cryo-ET data, enabling high-throughput segmentation and training of CNNs.

DeePiCt is a deep-learning framework for segmenting and localizing macromolecular complexes in cryo-electron tomograms, showing effectiveness in identifying low-abundance structures across species.

The paper determines the structure of UAF bound to DNA and TBP to reveal how UAF selects RNA Polymerase I for ribosome biogenesis and mediates specific protein-DNA interactions.

DISCA uses deep learning to automatically cluster cryo-ET data into homogeneous structural subsets without templates or labels.

The paper determines the in-cell architecture of a transcribing and translating expressome in Mycoplasma pneumoniae using integrative structural methods.