Rosemary Yu

The paper improves genome-scale flux profiling in human cell metabolism by introducing a new method for exo-metabolite exchange flux calculation, enhancing the biological relevance of metabolic models.

This study shows DNA genomes had a stoichiometric selection advantage over RNA genomes in early life, due to efficiency in macromolecular composition, not chemical stability.

This paper integrates single-cell RNA-seq data to create a human corneal cell state meta-atlas and develops a machine learning tool to annotate cell states and identify key transcription factors.

This paper introduces a mathematical model to predict molecular behaviors in cell plasticity using omics time-series data and demonstrates its ability to make non-trivial predictions.

The paper investigates the non-random organization of flux control mechanisms in yeast metabolic pathways, identifying distinct regulatory strategies across different pathways.

This study shows that a single chromosome yeast strain has reduced ethanol metabolism and growth compared to wildtype.

The paper quantifies absolute gene expression profiles in yeast to show central carbon metabolism genes are regulated independently of global physiological cues.

This study benchmarks the accuracy and precision of intensity-based protein quantification methods in yeast using mass spectrometry.