Robert Lehmann

The paper maps RNA-DNA interactions in 16 human cell types, showing cell-type-specific and dynamic networks that correlate with gene regulation and disease traits.

The paper maps RNA-chromatin interactions in human prefrontal cortex, revealing co-regulatory changes linked to brain evolution and disease pathways.

The paper identifies transcriptional changes in the avian brain during visual imprinting using single-nucleus RNA sequencing, revealing cell clusters and lncRNAs linked to memory formation.

The paper develops a machine learning method to identify cis-regulatory element profiles and their sequence features during neuronal differentiation using single-cell ATAC-seq and RNA-seq data.

This study identifies novel RAB13+ endothelial and profibrotic mesenchymal cells in aged human bone marrow using single-cell RNA sequencing and spatial transcriptomics.

This paper introduces a method to predict perturbation responses in unseen cell types using cell-type-specific graphs, showing improved performance over existing methods.

This paper introduces a denoising diffusion model to predict and interpolate spatial transcriptomics data, enabling generative modeling of tissue slices.

This study establishes an HLA-based iPSC banking system for the Saudi population, demonstrating that a small number of iPSC lines can cover a significant portion of the population's HLA haplotypes.

scAEGAN unifies single-cell genomics data by adversarial learning of latent space correspondences, outperforming existing methods in integration and prediction tasks.

The paper examines molecular changes in Arabian pupfish during salinity acclimation, identifying both transient and long-term gene expression responses in different populations.

This paper introduces LIBRA, a neural network framework for integrating and predicting across paired single-cell multi-omics data, showing improved clustering resolution and predictive power.

scMomentum infers cell-type-specific regulatory networks and energy landscapes from single-cell transcriptomic data without needing temporal or perturbation experiments.

This paper presents a chromosome-scale genome assembly for the orange clownfish, providing a valuable resource for studying reef fish ecology and evolution.