Suresh Sudarsan

The paper investigates how genetic variant interactions in yeast activate latent metabolic pathways and modulate phenotypic outcomes during sporulation.

The paper investigates high cell density physiology in Escherichia coli, revealing a trade-off between resistance and persistence through transcriptional analysis and machine learning.

This paper uses machine learning to analyze transcriptomic data from Yarrowia lipolytica under various industrial stresses, identifying regulatory modules and their responses to environmental changes.

This study investigates Yarrowia lipolytica's response to repeated oxygen limitations using a multi-omics approach, revealing that post-transcriptional regulation dominates its adaptation to industrial conditions.

The paper designs synthetic control circuits in yeast to stabilize vanillin-β-glucoside production over multiple generations, achieving higher yields in fermentation.

The paper develops a synthetic selection system in yeast to enrich for high-producing muconic acid variants by coupling production to cell fitness through a pH-tunable sensor-selector.