Jonas Simon Fleck

The paper uses a multiplexed single-cell transcriptomic screen to study how morphogen cues affect regional specification in human neural organoids, finding that timing, concentration, and combination of morphogens strongly influence cell type and regional composition.

CellFlow predicts single-cell phenotypes from complex perturbations using flow matching, demonstrating accuracy in cytokine stimulation, drug treatments, and developmental modeling.

This paper integrates 36 single-cell transcriptomics datasets from human neural organoids into a unified atlas to assess cell type coverage and compare organoid protocols with primary brain tissue.

The paper reconstructs epigenomic trajectories in human neural organoids from pluripotency to terminal cell states using single-cell histone modification profiling.

This paper creates a human endoderm organoid cell atlas by integrating single-cell transcriptomes from multiple organoid types to compare cell states with primary tissues and disease models.

The paper uses CRISPR and single-cell transcriptomics to screen ASD risk genes in brain organoids, identifying developmental defects and regulatory modules linked to autism.

This study uses single-cell genomics to analyze axolotl forebrain cell types, neurogenesis, and regeneration, identifying conserved neuron classes and injury responses.

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.

The paper uses single-cell genomic data from human cerebral organoids to infer gene regulatory networks and assess transcription factor roles in brain development.

A linear conditional random field over ordered protein-domain annotations finds biosynthetic gene clusters de novo more precisely than DeepBGC and runs over three times faster on one CPU.

This paper introduces VoxHunt, a computational method that maps single-cell genomic data from brain organoids to spatial reference data to assess patterning and cell composition.

This study uses single-cell genomics to compare brain development in humans, chimpanzees, and macaques, identifying human-specific gene regulatory features.