Sho S Takeshita

The paper introduces ioNERDSS, a Python tool that converts 3D atomic structures into coarse-grained models for simulating macromolecular self-assembly.

This paper introduces a membrane-driven biochemical oscillator that uses volume-to-surface area ratio to tune oscillation periods and validates it through computational and simulation studies.

The paper evaluates deep learning models for predicting noncovalent protein-carbohydrate interactions using a new dataset and metric, finding comparable performance but declining accuracy with longer carbohydrates.