Yara Seif

The paper develops a workflow to reconstruct dynamic transcriptional regulatory networks from public gene expression data using Bacillus subtilis as a case study.

This study uses machine learning to analyze RNA-Seq data from multiple Salmonella Typhimurium strains, revealing transcriptional modules and regulatory patterns across the pan-genome.

The paper extends an enzyme-constrained GEM framework to include amino acid usage in yeast, showing how metabolic proteome demands affect amino acid availability and metabolic robustness.

The paper identifies regulons of five two-component systems in E. coli using RNA-seq and ChIP-exo data, revealing novel regulatory relationships and non-cognate inducers.

The paper reconstructs the Fur pan-regulon in E. coli strains, revealing core, accessory, and unique regulons and their functional diversity.

BOFdat generates biomass objective function stoichiometric coefficients from omic data and calculates maintenance costs.