Kotaro Shirakawa

This study identifies the non-spike R204P mutation in the SARS-CoV-2 Omicron XEC variant as a driver of increased inflammation and pathogenicity through NF-κB activation.

This paper introduces CoVFit, a protein language model that predicts SARS-CoV-2 variant fitness using spike protein sequences, identifying fitness-enhancing mutations and predicting emerging variants.

The paper presents nine alpaca nanobodies that recognize conserved hidden epitopes on SARS-CoV-2 spike proteins across variants and maintain neutralizing activity against escape mutations.

The paper develops NET-CAGE to detect nascent RNA 5-ends, identifies enhancer-promoter pairs, and reveals topological connections of cis-regulatory elements across cell types.