Mami Yoshimura

The paper develops a barcoded yeast collection to map genotype-phenotype relationships across genetic diversity, revealing genetic variants linked to chemical responses.

This paper identifies brilacidin as a novel antifungal agent effective against Cryptococcus neoformans, showing it reduces fungal survival in macrophages and potentiates existing antifungals.

The paper identifies genes whose overexpression is adaptive under stress in budding yeast, revealing cellular requirements influenced by genetic background and environment.

BIONIC integrates biological networks using deep learning to improve accuracy and scalability, identifying novel gene interactions in yeast.

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.

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.