Galit Lahav

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

The paper shows intermediate spinal cord progenitors are specified through neural plate dynamics and signaling, not direct morphogen exposure.

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.

MSModDetector identifies PTM patterns in individual ion mass spectrometry data by detecting mass shifts and using linear programming to infer modifications.

The paper shows that a bHLH circuit enables neural stem cells to choose astrocytic fate by integrating BMP and LIF signals and suppressing alternative fates.

The paper investigates how varying ERK activity levels influence proliferation in cells undergoing oncogene-induced senescence, finding intermediate ERK activity promotes maximal proliferation.

The paper identifies universal and cell type specific p53 DNA binding sites by analyzing 12 epithelial cell lines after ionizing radiation.

The paper uses linear programming to estimate modform distributions of proteins with multiple post-translational modifications, showing that combining bottom-up and top-down MS data reduces average modform range.

The paper uses a multi-modal proteomics approach to analyze PTMs of p53, revealing many modification sites but few distinct modified forms.