Anja Sieber

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

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

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

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.

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.

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

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.