Morgane Thomas‐Chollier

This study benchmarks bioinformatics methods for single-cell and spatial RNA-seq Nanopore long-read data, evaluating their accuracy, robustness, and scalability across different protocols and sequencing conditions.

The paper identifies transcriptional disruptions in dendritic cells from SLE patients, highlighting interferon-driven changes, impaired IL-10 signaling, and altered lipid metabolism as key factors in tolerance dysfunction.

The paper identifies CDKN1c/p57kip2 as a regulator of the transition from symmetric proliferative to asymmetric neurogenic divisions in spinal progenitors using single-cell RNA-seq data from chick embryos.

The paper compares regeneration of two complex structures in Platynereis, finding shared and distinct molecular, cellular, and morphological features in their regenerative processes.

AsaruSim simulates synthetic single-cell Nanopore long-read datasets to evaluate isoform detection methods using human PBMC data.

The paper introduces forkedTF, a tool to create FPWM and F-Logos for modeling TF dimer binding sites, and provides precomputed resources in MethMotif 2024.

The paper shows that bacterial pore-forming toxins induce alternative splicing of CIRBP and SRSFs, altering cell response to Listeria infection.

Eoulsan 2 updates a workflow manager to support bulk, long-read, and single-cell transcriptomics analyses with improved infrastructure and module development.

The paper quantifies how cis-acting genetic variation affects chromatin accessibility, histone modifications, and gene expression in Drosophila embryos, finding that much of this variation does not propagate to gene expression.

The paper introduces two computational methods for analyzing complex biological models and applies them to predict T cell responses to checkpoint inhibitors.

The paper develops a computational model of the Nodal and BMP2/4 signaling pathways in sea urchin embryos, showing BMP dominance and the importance of Smad activation rates in dorsal-ventral patterning.

The paper introduces Var-tools, a framework for predicting the impact of regulatory variants on transcription factor binding, with four case studies demonstrating its functionality.

This study develops synSTARR-seq to analyze how DNA sequence and shape affect transcriptional activity and noise using synthetic GR binding sites.

The paper introduces matrix-clustering, a tool that reduces redundancy and clusters transcription factor binding motifs from multiple sources, improving interpretation of motif collections.