Ngaam J. Cheung

Residue communities reveal evolutionary signatures of γδ T-Cell receptor

The paper identifies functionally important residues in γδ T-cell receptors using evolutionary couplings, revealing residue communities that correlate with activation states and binding modes.

Accurate prediction of protein torsion angles using evolutionary signatures and recurrent neural network

This paper introduces ESIDEN, a recurrent neural network that uses evolutionary signatures to predict protein torsion angles with high accuracy, improving upon existing methods.

Leri: a web-server for identifying protein functional networks from evolutionary couplings

Leri identifies protein functional networks from evolutionary couplings by analyzing residue communities, enabling studies on protein evolution and function.

Sibe: a computation tool to apply protein sequence statistics to folding and design

Sibe is a computational tool that uses protein sequence statistics for folding and design, demonstrating its ability to capture conserved couplings and aid in rational protein design.

De novo protein structure prediction using ultra-fast molecular dynamics simulation

This paper introduces NiDelta, a de novo protein structure predictor using deep learning and molecular dynamics, showing high accuracy in predicting tertiary structures of proteins.