Rani K. Powers

This paper introduces SOPHIE, a method using generative neural networks to distinguish common from specific transcriptional responses across datasets.

This paper develops a deep learning model to extract evolutionary information from glycans, revealing insights into host-pathogen interactions and phenotypic diversity.

GSEA-InContext Explorer is a Shiny app that performs and visualizes gene set enrichment analysis using two methods, allowing users to compare results across experiments and identify significant gene sets.

This study identifies sequential waves of oligodendrocyte and NG2 cell fate specification in zebrafish spinal cord through distinct levels of Hedgehog signaling and Notch activity.

GSEA-InContext identifies common and experiment-specific gene set enrichment patterns by comparing an experiment to a background compendium of transcriptomic data.