Naomi Ziv

The paper investigates stochastic switching between two heritable cell states in Candida albicans using microfluidics and fluorescent reporters, identifying two stochastic steps involving Wor1 autoregulation.

The paper introduces PIE, a software tool for automatically tracking microbial colony growth in low-resolution images, enabling large-scale analysis of growth and fluorescence properties.

The paper shows that opaque cells in C. albicans up-regulate proteases and transporters to efficiently use proteins as nitrogen sources, enabling white cells to proliferate in mixed cultures.

This study quantifies vertical and horizontal pleiotropy in yeast using single-cell phenotyping, revealing context-dependent trait correlations and implications for evolutionary medicine.