Jérémie Breda

Transcription controls chromatin-nuclear lamina contacts through distinct Lamin A and LBR tethering mechanisms

This study shows that transcription inhibition rapidly and reversibly rewires chromatin-nuclear lamina contacts through distinct Lamin A and LBR tethering mechanisms.

Coordinated control of genome-nuclear lamina interactions by Topoisomerase 2B and Lamin B receptor

The paper identifies TOP2B as a regulator of genome-nuclear lamina interactions, showing its role in partitioning genomic regions between the nuclear lamina and interior, with LBR playing a complementary role.

The regulatory grammar of human promoters uncovered by MPRA-trained deep learning

This paper introduces PARM, a deep learning model trained on MPRA data to predict human promoter activity and identify TF binding preferences, revealing positional and functional differences in regulatory grammar.

The protooncogene Ski regulates the neuron-glia switch during development of the mammalian cerebral cortex

The paper investigates the role of the protooncogene Ski in regulating the neuron-glia switch during mammalian cerebral cortex development and identifies its interaction with the BMP signaling pathway.

Temporal and sequential transcriptional dynamics define lineage shifts in corticogenesis

The paper maps transcriptional dynamics in murine cortical development, identifying lineage shifts and gene regulatory networks in neural stem cells, basal progenitors, and newborn neurons.

A novel approach to single cell analysis to reveal intrinsic differences in immune marker expression in unstimulated macrophages from BALB/c and C57BL/6 mouse strains

This study uses single-cell RNA sequencing to compare gene expression variation in unstimulated macrophages from BALB/c and C57BL/6 mice, revealing intrinsic differences and polarization patterns.

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network.

The paper identifies widespread transcription initiation at microsatellites across species and develops deep learning models to predict STR-associated transcription and its impact on disease variants.

Bayesian inference of the gene expression states of single cells from scRNA-seq data

This paper introduces a Bayesian normalization method for scRNA-seq data that improves clustering and differential expression analysis by accounting for biological and technical noise.

Automated Incorporation of Pairwise Dependency in Transcription Factor Binding Site Prediction Using Dinucleotide Weight Tensors

This paper introduces a new model for transcription factor binding site prediction that accounts for pairwise dependencies between positions, outperforming existing methods on ChIP-seq and HT-SELEX data.