Félix Naef

The paper investigates how selective tRNA charging defects affect translation and stress responses using inhibitors in different cell types.

Low- and high-dose anisomycin confine ribosome collisions to a dose-shifted zone just past the start codon, whereas 30 min after UV, collisions appear more dispersed and favor highly translated mRNAs.

The paper analyzes daily gene expression rhythms in the regenerating colon using single-cell transcriptomics, revealing cell-type specific patterns and identifying a resource for future studies.

The paper uses single-mRNA imaging and modeling to show that translation initiation and elongation rates are coupled, maintaining low ribosome density and translational homeostasis.

CoPhaser models biological cycles in scRNA-seq by decomposing data into periodic and non-periodic sources, revealing insights into cell cycle dynamics and other periodic processes across diverse contexts.

This paper introduces scRitmo, a method to infer circadian phases and quantify biological desynchrony from single-cell transcriptomes, showing improved performance over existing methods.

This study shows that cell cycle inhibition in mouse gastruloids preserves core developmental processes but alters lineage proportions and differentiation timing.

The paper introduces Riboclette, a conditional deep learning model that predicts ribosome footprints under amino acid deprivation and identifies key codons and motifs driving translation stalling.

This study shows that BCAA starvation causes codon-specific ribosome stalling, affecting translational dynamics and protein output in mammalian cells.

This paper introduces a statistical RNA velocity model that improves dynamical consistency and inference of cell cycle speed from scRNA-seq data.

This study introduces RiboGL, a model combining graph and recurrent neural networks to predict ribosome density from mRNA secondary structure, outperforming existing methods.

Circadian phase inference of 914 GTEx donors reveals sex- and age-dependent rhythmic gene expression programs across 46 human tissues.

This study analyzes the circadian nuclear and cytoplasmic transcriptomes in mouse liver to understand temporal regulation of RNA processing and stability.

The paper measures single-cell mRNA dynamics of core-clock genes in mouse fibroblasts and develops a probabilistic model to decompose mRNA variability, showing circadian phase is encoded post-transcriptionally.

The paper investigates circadian rhythms in liver chromatin organization and transcription, finding both clock-controlled and clock-independent chromatin structures regulate physiological functions.

This study uses single-cell RNA-seq to show that many liver genes are both zonated and rhythmic, with multiplicative space-time effects, revealing spatio-temporal compartmentalization of liver function.

This study examines how sleep deprivation affects gene expression and chromatin accessibility in mice, revealing long-term genomic regulatory changes.

This study infers coupling and non-linear dynamics between circadian clocks and cell cycles from single-cell microscopy data, revealing temperature-independent, evolutionarily conserved phase-locked states.

The paper investigates ribosome dwell times and their relationship with aminoacyl-tRNA levels in mammals, finding that codon usage and tRNA abundance influence translation efficiency.

The paper quantifies how SMAD4 and SMAD2 dynamics relate to ctgf gene activation kinetics in single cells using live imaging and temporal analysis.

The paper investigates how circadian gene expression is regulated across tissues by analyzing transcription factor activity rhythms and chromatin interactions in mouse tissues.