Alexandra J. Lee

CF-Seq provides a web tool for re-analyzing CF pathogen RNA-seq data, enabling efficient filtering, visualization, and hypothesis generation across multiple studies.

The paper analyzes transcriptional patterns of core and accessory genes in P. aeruginosa strains using a transcriptome compendium, revealing stable core gene expression patterns across strains.

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

The paper simulates gene expression compendia to show that technical variability masks biological signals, but correction methods help when few experiments are combined, while more experiments make detection easier without correction.

The paper reports results from the CAFA3 challenge, showing improved computational protein function prediction and new annotations for over 1000 genes through experimental screens in C. albicans, P. aureginosa, and Drosophila.