Pablo Yubero

The paper presents a framework using genome-scale metabolic reconstructions to interpret genotype-to-phenotype associations and identifies limitations in phenotype prediction in metabolism.

The paper develops a statistical framework to predict fitness costs of complex mutations by identifying key molecular predictors using RNA polymerase mutations in E. coli.

The paper quantifies how global transcriptional regulation affects gene expression across 700 genes in E. coli and shows that gene position near the origin of replication correlates with sensitivity to transcriptional resources.