Lucas Pelkmans

Multiplexed embryo profiling links cellular state to zygotic genome activation in single cells

The paper introduces 3D-4i imaging and analysis to study cell cycle dynamics and transcriptional output during zygotic genome activation in zebrafish embryos.

Shield-4i: A Whole-mount Multiplexed Imaging Platform for Studying Multiscale Information Flow in 3D Multicellular Systems

Shield-4i enables high-throughput, subcellular-resolution imaging of whole-mount structures to study multiscale information flow in multicellular systems.

Fractal: Towards FAIR bioimage analysis at scale with OME-Zarr-native workflows

Fractal introduces a task specification and platform for scalable, reproducible OME-Zarr-native bioimage analysis workflows, demonstrating reproducibility across diverse imaging data and clinical settings.

Multiscale chromatin dynamics and high entropy in plant iPSC ancestors

The paper investigates chromatin dynamics in plant protoplasts during dedifferentiation, finding rapid multiscale changes influenced by nutrients and a decline in chromatin entropy over time.

Learning Single-Cell Perturbation Responses using Neural Optimal Transport

This paper introduces a method to predict single-cell perturbation responses using neural optimal transport, showing improved performance over existing methods on drug-treated cells.

OME-Zarr: a cloud-optimized bioimaging file format with international community support

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

Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps

The paper introduces CAMPA, a deep-learning framework for analyzing subcellular organization changes, and applies it to human cells to study how perturbations affect subnuclear organization and membraneless organelles.

scROSHI - robust supervised hierarchical identification of single cells

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

Robust and Versatile Arrayed Libraries for Human Genome-Wide CRISPR Activation, Deletion and Silencing

The paper constructs genome-wide CRISPR libraries for gene ablation, activation, and silencing with high efficacy and reports novel gene regulators and modifiers.

Multimodal spatiotemporal phenotyping of human organoid development

This paper develops a multimodal approach to study human retinal organoid development, integrating spatial, transcriptomic, and chromatin accessibility data to create a virtual atlas of retinal development.

Characterization of the neurogenic niche in the aging dentate gyrus using iterative immunofluorescence imaging

This study uses iterative immunofluorescence imaging to analyze age-related changes in the dentate gyrus niche, identifying reorganization and microenvironmental changes affecting neurogenesis in mice.

Nuclear RNA concentration coordinates RNA production with cell size in human cells

The paper shows that mammalian cells maintain constant RNA concentrations by adjusting mRNA synthesis and degradation rates in response to changes in cell size.

SCIM: Universal Single-Cell Matching with Unpaired Feature Sets

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.

KDML: a machine-learning framework for inference of multi-scale gene functions from genetic perturbation screens

KDML predicts multi-scale gene functions from genetic perturbation screens, outperforming traditional methods and identifying clinically relevant gene function associations in colorectal cancer.

Cellular state determines the multimodal signaling response of single cells

The paper shows that cellular state influences the multimodal signaling response to growth factors, enhancing context-aware decision making.