Nils Blüthgen

Perturb-seq identifies TCF7 as a central nexus linking MAPK- and Wnt-driven gene expression

The paper uses Perturb-seq to identify TCF7 as a key integrator of MAPK and Wnt signaling pathways through a feedback loop with EGR1.

The Establishment of Cell-Type Specific Gene Regulation in the Sea Urchin Embryo

This study creates a single-cell atlas of gene expression, transcription, and chromatin accessibility in sea urchin embryos, revealing dynamic regulatory elements and lineage-specific gene activation patterns.

Rewired type I IFN signaling is linked to age-dependent differences in COVID-19

This study identifies age-related rewiring of type I IFN signaling in immune cells linked to increased inflammation and altered antibody responses in COVID-19.

Reporter-based screening identifies RAS-RAF stabilizing mutations as drivers of resistance to broad-spectrum RAS inhibition in colorectal cancer

Spike-in enhanced phosphoproteomics uncovers synergistic signaling responses to MEK inhibition in colon cancer cells

The paper introduces SPIED-DIA, a phosphoproteomics method, to identify synergistic signaling responses in colon cancer cells to MEK inhibition and growth factor stimulation.

Subcellular mRNA kinetic modeling reveals nuclear retention as rate-limiting

The paper measures mRNA flow rates between subcellular compartments in mouse embryonic stem cells and identifies nuclear retention as the rate-limiting step for many mature mRNAs.

RUCova: Removal of Unwanted Covariance in mass cytometry data

RUCova removes unwanted covariance in mass cytometry data using multivariate regression and PCA, preserving biological signals and improving analysis accuracy.

Quantitative modelling of signaling in aggressive B cell lymphoma unveils conserved core network

The paper models BCR signaling in B cell lymphoma cells to identify conserved network structures and crosstalk mechanisms.

scPerturb: Harmonized Single-Cell Perturbation Data

The paper harmonizes single-cell perturbation datasets and introduces E-statistics for analyzing perturbation effects across diverse data sources.

Targeted Perturb-seq Reveals EGR1 and FOS as Key Regulators of the Transcriptional RAF-MAPK Response

This study uses targeted Perturb-seq to identify EGR1 and FOS as key regulators of the transcriptional RAF-MAPK response by constructing a directional interaction network.

Identifying mutant-specific multi-drug combinations using Comparative Network Reconstruction

The paper presents a pipeline to identify effective and selective multi-drug combinations by reconstructing mutant-specific signaling networks and predicting their impact on cell viability.

Insights into standards of care: dexamethasone and antibodies against COVID-19 in hamster models

The paper evaluates dexamethasone and anti-SARS-CoV-2 antibodies in hamster models, showing reduced viral burden with antibodies and anti-inflammatory effects with dexamethasone, with synergistic benefits when combined.

Identifiability and experimental design in perturbation studies

The paper develops a framework to optimize perturbation experiments by identifying minimal perturbation sets that maximize network parameter inferability.

Robust network inference using response logic

This paper introduces a network inference method based on response logic that outperforms existing approaches in benchmark challenges and generates plausible network hypotheses from perturbation data.

Comparative Network Reconstruction using Mixed Integer Programming

This paper introduces a computational method to reconstruct signaling networks from incomplete perturbation data and identify differences between networks in sensitive and resistant cells.

Modelling Signalling Networks from Perturbation Data

The paper develops a modified MRA method to model signalling networks from incomplete perturbation data and applies it to study SHP2's role in colon cancer cell lines.

Classification Of Gene Signatures For Their Information Value And Functional Redundancy

The paper defines a set of informative gene signatures from pan-cancer data and introduces InfoSigMap to visualize their compositional and functional redundancies.

Noise control is a primary function of microRNAs and post-transcriptional regulation

The paper shows microRNAs primarily control expression noise rather than repress protein levels, and this noise control is widespread across species.

Perturbation-response genes reveal signaling footprints in cancer gene expression

This study introduces PROGENy, a method that improves pathway activity inference from gene expression by using perturbation experiments, showing better accuracy than existing methods.