Hideo Nakano

This study identifies and characterizes monoclonal antibodies from rabbit B cells that bind intestinal bacteria, demonstrating their broad specificity and potential for therapeutic applications.

The paper screens translation-enhancing peptides (TEPs) in E. coli and develops a machine learning model to predict their activity, showing strong correlation with experimental results.

The paper introduces SMART, a single-molecule display platform for enzyme engineering, and demonstrates its application in evolving D-amino acid oxidase with improved substrate specificity.

The paper shows that the SKIK peptide tag enhances translation of proteins with ribosome arrest peptides like WPPP by reducing translational stalling, both in vitro and in vivo.

The paper develops a method combining PURE ribosome display, NGS, and microbial secretion to identify high-affinity antibody variants.

The paper constructs predictive models to determine if genes respond to AoXlnR expression changes using DNA shape features around binding motifs.

This study identifies substrate preferences of human transglutaminase 1 using cDNA display and next-generation sequencing, revealing a high-reactivity peptide and potential new substrates.

The paper develops a cost-effective method for epitope mapping using PURE ribosome display combined with NGS and bioinformatics, identifying the 'DVPDY' epitope in hemagglutinin.

This paper introduces a method to increase gene expression from linear DNA templates in cell-free systems by using DNA-binding proteins, achieving significant yield improvements in both E. coli and Vibrio natriegens.