A public database and analysis platform for ribosome profiling data. The goal is to make Ribo-Seq data reusable - standardized processing, curated metadata, and tools that let researchers ask questions across thousands of experiments instead of just their own.
A new data structure for representing translation. Instead of treating each transcript as independent, RDGs capture how ribosomes navigate between alternative paths through a locus - more accurate for biology, better for annotation.
Building pipelines to incorporate Ribo-Seq evidence into automated genome annotation workflows at scale. The challenge: making translation data computationally tractable for thousands of genomes while maintaining biological accuracy.
Working on consistent nomenclature for translated regions. "Translon" as a single term for regions of active translation - replacing the confusing mix of ORF, CDS, uORF, dORF, etc.