Tomiko T Oskotsky

High-throughput sequencing enables efficient processing of DNA and RNA samples in batches, but batch effects can obscure true biological signal. We propose using anticlustering as an automated method to assign samples to balanced batches, m…

Endometriosis is a prevalent, complex, inflammatory condition associated with a diverse range of symptoms and comorbidities. Despite its substantial burden on patients, population-level studies that explore its comorbid patterns and heterog…

Endometriosis is an enigmatic disease whose diagnosis and management are being transformed through innovative surgical, molecular, and computational technologies. Integrating single-cell and other omic disease data with clinical and surgica…

Endometriosis is a chronic, estrogen-dependent condition affecting over 190 million women globally, characterized by the ectopic presence of endometrial-like tissue that leads to inflammation, pain, and infertility. Despite its prevalence, …

This perspective explores the transformative potential of data-driven insights to understand and address women's reproductive health conditions. Historically, clinical studies often excluded women, hindering comprehensive research into cond…

Existing medical treatments for endometriosis-related pain are often ineffective, underscoring the need for new therapeutic strategies. In this study, we applied a computational drug repurposing pipeline to stratified and unstratified disea…