Stephan Preibisch

The paper shows that organelle volume in C. elegans oocytes influences spindle positioning during meiosis by affecting the central ball of organelles.

The paper presents the complete connectome of the Drosophila male central nervous system and compares it to the female connectome, identifying sex-specific and dimorphic neuronal types.

The paper presents a spatial omics framework combining protein and RNA imaging with machine learning to classify brain cell types and discover structural features at tissue scale.

PEELing provides a platform for analyzing spatially-resolved proteomics data with quality assessment, contamination removal, functional annotation, and visualization tools.

The paper introduces STIM, a framework for visualizing and aligning spatial transcriptomics data, demonstrating its use on mouse and human tissue samples.

A FIB-SEM connectome of the male Drosophila right optic lobe sorts ∼53,000 neurons into 727 types, with neurotransmitter predictions and 577 matched split-GAL4 lines.

This paper introduces cycleHCR technology for high-resolution spatial transcriptomics and protein imaging in thick tissues, demonstrating its application in mouse embryos and brain slices.

The paper releases high-resolution 3D imaging and nucleus segmentations of seven tissues from a P7 mouse using FIB-SEM and machine learning.

The paper develops a smFISH method with computational staging to study transcription dynamics in C. elegans embryos and finds that the DCC reduces dpy-23 transcription frequency.

This study uses mCherry-titin mice to visualize sarcomere dynamics during skeletal muscle development and injury repair, revealing titin mobility and localization patterns in myocytes.

This paper describes OME-Zarr, a cloud-optimized bioimaging file format developed through community collaboration to improve scalability and data access.

This paper presents optimized CPU and GPU implementations of the recursive least-squares algorithm for training spiking neural networks, enabling faster training of large-scale models.

Roughly 23 thousand traced neurons and 10 million TBars of the male Drosophila nerve cord, reconstructed from electron microscopy, typed, and queryable in neuPrint down to motor neurons.

RS-FISH detects FISH spots accurately and efficiently in 2D and 3D images, supporting applications like smFISH and spatial genomics.

This paper introduces a method for automated lineage reconstruction in developing embryos using sparse annotations, achieving 75.8% accuracy on mouse embryos compared to 31.8% previously.

This paper introduces FRC-QE, a 3D image quality metric for cleared organoids, showing it robustly captures clearing efficiency differences across protocols and microscopy modalities.

The paper quantifies the spatial activity of a Drosophila enhancer through sequence mutagenesis and image analysis, revealing dense regulatory information and novel regulatory logic.

The paper investigates how p53-mediated transcriptional responses to DNA damage are modulated by stochastic bursting frequency, identifying distinct gene expression archetypes.

BigStitcher reconstructs high-resolution image datasets from cleared and expanded biological samples, compensating optical distortions for single-cell analysis.

The paper uses multi-view light-sheet imaging and a new tracking tool to reconstruct cell lineages and behaviors during crustacean limb development, revealing how cell proliferation and division orientation drive limb outgrowth.