Franziska Michor A

This study identifies BRD2 as a co-targetable vulnerability with PI3K/AKT inhibitors in breast cancer, showing that BRD2 phosphorylation is required for chromatin binding and that targeting BRD2 enhances drug efficacy.

This study shows that punctuated mutagenesis in cancer enhances adaptation by facilitating crossing of fitness valleys through clustered mutations.

This paper develops a digital twin model to optimize epigenetic therapies in triple-negative breast cancer by simulating treatment responses and identifying effective drug combinations.

MBTA uses flow matching to address structural mismatch between molecular modalities, improving cross-modal translation and enabling multimodal analysis in single-cell data.

This study identifies hypertranscription as a vulnerability in H3K27M-driven diffuse midline gliomas, showing ATR inhibition effectively targets this feature in preclinical models.

This study shows that multi-region neurospheres from glioblastoma tumors retain spatial diversity and drug response patterns linked to their original biopsies, highlighting their importance for modeling intratumor heterogeneity.

The paper identifies optimal radiotherapy schedules to reduce metastasis by combining mechanistic modeling and machine learning with in silico clinical trials.

BESTDR quantifies drug response mechanisms using Bayesian modeling of cell state transitions, improving accuracy in dose-response analysis across cell lines.

The paper investigates how p21 transcription variability arises through an incoherent feedforward loop involving p53 and MDM2, showing it enables rapid p21 induction and treatment-tolerant cell states.

This study uses optimal transport analysis on scRNA-seq data to reconstruct EMT trajectories in MCF10A cells, identifying three distinct fates and novel genes associated with different EMT states.

The paper identifies and characterizes LNCSOX17, a lncRNA essential for human endoderm formation, showing its role in regulating transcriptome and differentiation.

The paper introduces BB-QTL mapping to study complex traits in yeast, revealing polygenic, pleiotropic, and epistatic genetic architectures with increased sample size.