Erik van Nimwegen

This study shows E. coli rapidly remodels its proteome during early starvation, with gene expression patterns in the first 10 hours determining long-term stress tolerance.

The paper quantifies how growth rate and protein production fluctuations contribute to gene expression noise in E. coli, finding growth rate fluctuations are largely independent and decrease with mean growth rate.

RealTrace is a Bayesian method that removes measurement noise from time-lapse microscopy data to reveal biological dynamics, showing fluctuating growth rates and gene expression in single cells.

Bonsai provides a tree-based visualization method for single-cell omics data that accurately represents distances and structures without distortion, offering novel biological insights.

The paper shows that growth rate affects the sensitivity of gene regulatory switches in E. coli, with experiments confirming theoretical predictions about inducer concentration thresholds.

The paper quantifies single-cell gene expression dynamics of LexA target promoters in E. coli under DNA damage, showing stochastic bursts driven by transient LexA concentration dips.

This paper introduces a method to partition single-cell RNA-seq data into statistically distinct gene expression states with no tunable parameters, showing it recovers optimal partitions on synthetic data and identifies subtle substructure in real data.

The paper reanalyzes data from Shen et al. to argue that most synonymous mutations in yeast genes are not deleterious, challenging their original conclusions about fitness effects.

RCRUNCH improves eCLIP data analysis to identify RNA-binding protein binding sites and motifs, creating a comprehensive resource of in vivo-bound RBP sequence motifs.

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.

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.

The paper creates a central repository for zebrafish developmental genomics data, identifies new cis-regulatory elements, and compares regulatory elements between zebrafish and mouse.

The paper introduces MAPP, a method to infer RNA-binding protein impacts on pre-mRNA processing from RNA-seq data, revealing co-regulation of splicing and polyadenylation.

The paper shows that subpopulations of sensorless bacteria influence fitness in fluctuating environments by affecting growth lags through gene expression noise.

The paper develops a method for quantitative analysis of fluorescence flow cytometry data in bacteria and introduces an open-source tool for this purpose.

The paper refutes critical claims about their double-adder model of E. coli cell cycle control by demonstrating errors in the opposing analysis and discussing implications for cell cycle models.

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.

This study identifies a double-adder mechanism that coordinates division and replication cycles in E. coli by measuring growth, division, and replication in single cells.

The paper quantifies transcriptional noise in E. coli across growth conditions and shows that noise is shaped by regulatory propagation from transcription factors.

Crunch automates ChIP-seq analysis and identifies regulatory motifs, finding that TFs either use single motifs or multiple co-occurring motifs in binding peaks.

The paper develops PAQR and KAPAC to analyze PAS use and motif activities in RNA-seq data, identifying Polypyrimidine tract binding protein 1 as a regulator of PAS choice in glioblastoma.

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.

The paper uses single-cell sequencing and mathematical modeling to estimate miRNA target parameters and uncover their in vivo hierarchy.

This study shows that EWSR1 prevents DNA double-strand breaks by binding to intronic regions in its own locus and maintaining genomic stability.