Akira Onoda

N-Terminal Alkylation of Proteins with Triazole-4-carbaldehyde for Targeted Liposome Engineering

This paper develops a method to attach proteins to liposomes via N-terminal alkylation using TA4C, enabling targeted delivery to EGFR-overexpressing cells.

Probe-Based Identification of Metal-Binding Sites Using Deep Learning Representations

PRIME is a deep learning framework that predicts metal-binding sites in proteins by integrating evolutionary and structural signals, achieving high accuracy across various metal ions.

Accurate and Rapid Prediction of Protein pKa: Protein Language Models Reveal the Sequence-pKa Relationship

This paper introduces pKALM, a deep learning model for rapid and accurate prediction of protein pKa values, achieving high speed and performance across various residues and termini.

PsiPartition: Improved Site Partitioning for Genomic Data by Parameterized Sorting Indices and Bayesian Optimization

PsiPartition improves genomic data partitioning using parameterized sorting indices and Bayesian optimization, outperforming existing methods on simulated and empirical datasets.

Fast and Accurate Prediction of Intrinsically Disordered Protein by Protein Language Model

The paper introduces IDP-PLM, a method for predicting intrinsically disordered proteins using protein language models without relying on multiple sequence alignments, achieving state-of-the-art performance.