Ashwini Oke

The paper evaluates yeast and nematode high-throughput assays for identifying reproductive toxic environmental chemicals and finds moderate to strong correlations with mammalian in vivo data.

This paper introduces a high-throughput method for quantifying Drosophila fecundity using automated imaging and transfer systems, achieving high accuracy and efficiency in fecundity assays.

The paper screens 133 chemicals for reproductive toxicity using C. elegans assays and compares results with ToxCast data, identifying 13 toxicants including QACs.

This paper develops a framework combining CNN and unsupervised learning to map genotype to vacuole morphology in yeast, identifying 4 phenotypic groups with 85% purity and 80% prediction accuracy.

This study shows that synaptonemal complex proteins influence mismatch repair during meiosis, leading to increased post-meiotic segregation in mutants lacking these proteins.