Hamid Safizadeh

The paper benchmarks structure descriptors and similarity coefficients using chemical-genetic interaction data to improve compound function prediction.

The paper develops CG-TARGET to predict compound biological processes by integrating chemical-genetic and genetic interaction networks, showing improved accuracy and FDR control.

The paper introduces MOSAIC, a database and web resource for chemical-genetic interaction data, enabling mode-of-action prediction and discovery of compound effects in yeast.

This study develops a yeast-based chemical-genetic screening system to annotate compound functionality across biological processes and identifies compounds with dual modes of action.